Read these as sequential gates. Realization handles liquidity and legal availability; follow-through handles intent; allocation handles cause choice; deployment handles the timing of actual grants by the deadline.
where do the defaults come from? Explain, reference, link (maybe as tooltips)
This may leave legally awkward, politically controversial, or non-lab-compatible work underfunded.
this needs fleshing out -- not sure what this is about
People who could puncture the rumor may also be financially incentivized not to alienate future donors.
I don't see how this would 'alienate future donors'?
. Or use + Suggest entry above to open a GitHub issue.
the 'suggest entry' is now going to a dead GH page -- find a better approach and solution
Three explicit flags that would substantially revise the estimates: (1) better proxy validity research (reversal learning, parental care as welfare indicators); (2) new data on understudied invertebrates; (3) theoretical advances o
can these be restated as questions?
The load-bearing belief is that neuron counts are only a defensible proxy for moral weight if they reliably correlate with the welfare-relevant capacities organisms actually posse
Better stated as a question ... something like "Do neuron counts reliably correlate with the welfare-relevant capacities organisms actually possess?" (of course 'reliably' probably would need operationalization, and this elides the possibility that it may "reliably correlate" but the correlation may be low)
Three explicit cruxes structuring the entire cross-cause model: (1) animals' moral weights relative to humans; (2) expected value of the long-run future; (3) preference for making a difference vs. expected value. Cause rankings reve
these are good, but can they be separated out and flexhed out and made more explicit?
The load-bearing belief is that any significant moral weight for animals, combined with Rethink Priorities' finding that corporate animal welfare campaigns are ~1000x more cost-effective than top global health interventions (e.g. AMF), implies Open Phil should prioritize animal welfare in neartermism. The author's position would change if the moral weights / welfare-range estimates favoring animals were substantially lower, or if a defensible reason were given for valuing human welfare units far above animal welfare units purely on species membership. The author explicitly asks what would have to change in OP's views to NOT prioritize animal welfare.
Not sure this one is an actual crux, rather an attempt to draw out Open Phil (now CG) on their moral weighting
the moral-weighting framework for suffering: whether one prioritizes duration of welfare improvement or the intensity/severity of suffering averted.
'prioritizes' is not clear here. Do they better operationalize this ... how would it be decided/measured?
What belief changes would actually alter donations or work — and what are the poster's actual cruxes? Author foregrounds room for more funding and marginal value.
meta -- not an actual crix
The load-bearing belief is that no compelling cost-effectiveness case exists for the alternatives; a promising cost-effectiveness estimate for institutional meat reduction campaigns would make the author excited about (and supportive of reallocating funding toward) them. To me, to be excited about such campaigns I'd need to see a promising cost-effectiveness estimate. High Shortlist EA Forum Did corporate campaigns in the US have any counterfactual impact? A quantitative model verified No — published 2019, before 2024 window Karolina Sarek 2019-06-24 Key uncertainty
clarify -- hard to read this
The estimated counterfactual impact of US corporate cage-free campaigns (2.1-10%) is load-bearing on the price elasticity of egg demand, a parameter drawn from a literature review with only ~13 observations.
this is a fairly well-defined operationalized crux. It's old, but I guess 'we still are not confident'!
is load-bearing on the price elasti
'is load-bearing on' ... that's too jargony; state it more clearly
He would be persuaded toward global health if shown a defensible rationale for valuing one unit of human welfare so much more than animal welfare that it justifies Open Phil funding GH ~6x as much as AW —
this latter bit is closer to being a specific 'crux'. remember we want these stated as operationalizable questions,if possible. And try to find the single question crux that seems most important or most correlated to the others. You can have another column listing other cruxes raised.
The author's load-bearing claim
you don't need "the authors ... " ... just state their crux question ... obviously it's the author
y The author's recommendation hinges on whether furnished-cage advocacy is actually more cost-effective per unit welfare than cage-free advocacy. He remains skeptical despite his own estimate (2.84x), and his position would shift on whether advocacy costs scale linearly with producer costs, whether infrastructure lock-in blocks later cage-free transitions, and whether furnished-cage campaigns would undermine the cohesiveness of global laying-hen advocacy.
This one is getting good. It seems pretty relevant, but I want you to state it as an explicit opertionalizable question here.
What are the most important questions you'd want answered before deciding how, where, and when to give $20M?
too meta
The author's position that shrimp welfare rests on a weak evidentiary base
State the actual crux. Your description here is more about the implications of the crux.
You can state somewhat general grounds, but then give a specific instantiation if possible. E.g., something about whether one form of slaughter is more painful to shrimp than another, or whether analgesia is good evidence, etc.
Would update on: timelines, public/model concern for animals, indirect normativity, moral-circle expansion, and simulated-animal welfare.
this is too general/vague. I want explicit defined crixes. What is the specific question they are uncertain about, how would you measure it, and what decision would it change?
4. Are you or your coauthors especially exposed to a durable negative public signal?
This framing feels too negative and definitive for my taste. As some of the modeling and discussion gets at, a single 'negative public signal' should not be so damning as people seem to think.
Would update on: timelines, public/model concern for animals, indirect normativity, moral-circle expansion, and simulated-animal welfare.
What exactly is the crux here? You haven't explained it.
What are the most important questions you'd want answered before deciding how, where, and when to give $20M?
It's also not that explicit. It's kind of meta.
Outlines eight cruxes that would change the ideal balance among cause, within-cause, and cross-cause prioritization.
ok but too meta -- maybe name ONE crux here and/or flesh out rows?
What belief changes would actually alter donations or work — and what are the poster's actual cruxes? Author foregrounds room for more funding and marginal value.
This is more like meta. I don't think it's an actual crux
Whether safety interventions and welfare interventions conflict or create synergies.
This feels a bit vague and could be explained and specified better
Coverage by cause area — click to filter · amber = legacy AI cluster · green = Unjournal core & in-scope AI
Allow more sophisticated sorting, e.g., by relevance and then by date, or by some combination.
A living map of EA Forum and LessWrong posts containing explicit cruxes, "what would change my mind" statements, and decision-relevant uncertainties — structured to surface candidate Pivotal Questions for evaluation and synthesis.
Make it clear at the top when was this last updated, and how much has been spent in API credits and processing time.
Fund the Prize Pool
Note the existing prize pool ($3400) ... change this to 'expand'
These are illustrative examples. Final tournament questions are being finalized with Metaculus.
these have now been finalized. Maybe integrate some of them in?
Predict the Future of Animal Welfare
Put in the link here, make it clear it's live, make it prominent, and perhaps use some of the style and language from there and incorporate it into this page.
his will be Metaculus' first tournament focused entirely on animal welfare. Questions will cover topics like:
We should adjust this - it's the first funded tournament that focuses broadly on animal welfare (there was an unfunded tournament as well as one focused on cultured meat).
Animal welfare funders face a strategic question:
Cite this. https://forum.effectivealtruism.org/posts/bDqdfMXe6YuYnwMDA/good-tasting-alt-meat-is-a-scientific-problem-we-can-solve Perhaps give a tool tip or a little background to help make it clear that this is something being funded and of strong interest to major funders.
· compensation?
'compensation' tooltip not working
Email (optional, only if you'd like a reply)
add "And compensation for good feedback, if we offer it -- always grandfathered in" -- tooltip actually
When we evaluate a paper, the pieces — the paper itself, two or three evaluations, the ratings, the authors' response, any follow-ups — end up on separate pages, and you have to jump between them to follow the thread. I've been trying out ways to put the whole thing on one page instead. These are rough prototypes. The idea is a reading layer that sits alongside PubPub (which stays the system of record for DOIs, indexing, and so on), not a replacement — though I realise splitting things across two homes has its own costs. I'm honestly not sure any of this is better, and that's mostly what I'd like your help with.
this but at the top is a bit long and even though it condenses a bit it's still a bit bulky and keeps popping up again as we scroll down.
Also, I want this to clearly state at the top that most of this content, including the explanations, has been generated using AI, although I have been looking over it and adjusting
I think that alternative proteins may fall into this bucket. While it doesn’t meet my personal donation bar for an evidence-based intervention, I understand why it has absorbed large amounts of philanthropic money earmarked for animal welfare. It might just eventually work.
GPT5.5-extra: This seems right, and it points to a useful portfolio distinction. Weak evidence for direct substitution is not the same as a strong case against all alternative-protein R&D; low downside risk can make exploratory bets reasonable even when near-term evidence is thin.
The decision-relevant question is not just "is this evidence-based now?" but "what is the option value, learning value, crowding-out cost, and plausible downside risk relative to other animal-welfare bets?"
We (the EA animal welfare community) should be using significant resources to generate useful evidence. But simply funding the broad field of animal welfare science is likely to create scattered research results that are difficult to translate into action.
GPT5.5-extra: I agree with this direction. A useful design distinction is between (1) decision-question elicitation, (2) study design and data collection, (3) independent review/replication, and (4) translation into funding or implementation decisions.
"Taking ownership" should not mean collapsing these roles into a single interested evaluator. The highest-value infrastructure may be a pipeline with clear handoffs, independent review, public evaluation packages, and explicit decision thresholds.
All three intervention examples I give have been extensively discussed, recommended by charity evaluators, and financed by major funders.
GPT5.5-extra: This is an important point, but I would separate "widely recommended/funded" from "best marginal opportunity." A field can converge on interventions because they are legible, scalable, fundable, or coalition-friendly, not only because they have the strongest evidence.
That distinction matters for diagnosis: the problem may be less "people made bad calls" and more "the field lacks institutions that can generate, audit, and translate decision-relevant evidence before interventions become large funding defaults."
R&D should be the #1 priority right now, ahead of scaling existing work.
GPT5.5-extra: This is plausible, and I am sympathetic, but the post does not fully close the argument for "#1 priority." To make the case, I would want an explicit value-of-information comparison: how much better could targeted R&D make future funding decisions, how soon, at what cost, and relative to the best marginal scaling opportunities?
This is exactly the kind of question that seems well suited to animal-welfare evidence infrastructure: pre-specified decision-relevant questions, rapid review, and evaluation packages rather than scattered academic outputs.
The report is a few years old now, but even then we already had multiple strong studies showing that the availability of equivalent substitutes does not lead to major changes in meat consumption.
GPT5.5-extra: I would soften "equivalent substitutes" here. Peacock's review is mainly about current plant-based meat and hypothetical improvements in price/taste/convenience; it does not establish that actually equivalent future substitutes, cultivated meat, or precision-fermentation products would fail to substitute. It is stronger as evidence that current plant-based availability and many current interventions have weak or uncertain effects.
However, we have little evidence for this substitution effect.
GPT5.5-extra: I agree with the direction, but would phrase this as "limited and hard-to-interpret evidence" rather than simply "little evidence." There is evidence from current plant-based meat and meat-reduction interventions, but it is hard to generalize to future products or to settings where price/taste/convenience are genuinely competitive.
This is also a measurement problem: substitution across animal products, plant-based products, eating occasions, and longer-run market responses is difficult to estimate with standard demand data.
Related Unjournal/PQ context: https://uj-pba-workshop.netlify.app/
I do not feel comfortable supporting a blanket push for cage-free reforms, given the currently available data on what happens when farms/countries switch.
GPT5.5-extra: This conclusion depends on what "blanket push" means. I would distinguish: (1) poorly managed or abrupt transitions, (2) regulatory/corporate cage-free commitments with weak implementation support, and (3) mature higher-welfare cage-free or free-range standards. The evidence against (1) or (2) is not automatically evidence against (3).
This seems like a good place for a decision-relevant decomposition: mortality, painful morbidity, behavioral deprivation, transition costs, and implementation quality should be modeled separately rather than compressed into "cage-free yes/no".
A counterpoint I sometimes hear is that the difference in mortality between caged and cage-free systems disappears as farmers gain experience with cage-free systems.
GPT5.5-extra: The 2021 meta-analysis does more than gesture at this counterpoint: it analyzes 6,040 flocks and 176M hens and finds mortality in cage-free aviaries decreases with experience; in recent years it finds no significant mortality difference among indoor systems. That does not prove all cage-free transitions improve welfare, but it weakens the inference from early/high-mortality transitions to mature cage-free systems.
Source: Schuck-Paim et al. 2021, https://www.nature.com/articles/s41598-021-81868-3
These aren't sudden, painless deaths. Increased vent pecking itself is also a sign of increased environmental stress. Overall, this suggests that hens in the cage-free systems generally experienced more distress.
GPT5.5-extra: This is a reasonable concern if the CSES aviary result is representative, but I would avoid leaning too hard on this single-farm comparison as evidence about cage-free systems overall. The linked CSES system was one implementation at one commercial site, and the broader Schuck-Paim et al. 2021 dataset suggests mortality in aviaries falls substantially as producers gain experience.
The stronger statement is: transition quality and management can matter a lot, and mortality/vent pecking are important welfare proxies, but this particular comparison does not by itself settle overall cage-free welfare.
Sources: https://www.nature.com/articles/s41598-021-81868-3 and https://welfarefootprint.org/laying-hens/
When shrimp first hit the ice slurry, they perform sudden full-body contractions (tail flips), but this also happens if you first cut their head off (check the supplementary material for a video).
GPT5.5-extra: I read this as evidence that the tail flip is a ventral-nerve-cord reflex, not as a proposal to decapitate shrimp as a slaughter method. Weineck et al. 2018 transected shrimp and found that isolated abdomens began tail-flipping in ice slurry; cutting the segmental roots prevented the movement. Their interpretation is that this is locally neural and involuntary, not driven by higher central brain centers.
So the evidential role is narrow: tail flips alone should not be treated as strong evidence of either conscious distress or insensibility, because a similar movement can be generated after separation from the head. It does not show that ice slurry is humane; it weakens one simple behavioral proxy.
Source: Weineck et al. 2018, section 3.7, https://www.mdpi.com/2076-2615/8/9/158
Additionally, both studies implanted conductive electrodes in the test animals. It is plausible that this significantly affects how current flows through the shrimp's body.I also feel confused about what a signal from an electrode on a heart or a ganglion actually tells us. The plots of the recorded “power” are hard to interpret without a control signal to assess what the noise floor is.
GPT5.5-extra: Clarification after checking: Weineck et al.'s "ECG" was not a mammalian-style electrical ECG. It was an impedance measure of movement or fluid between leads over the heart, so amplitude tracks contraction/flow rather than subjective experience directly. The 2026 Somerville et al. preprint instead uses electrophysiological recordings from the supraoesophageal ganglion and operationalizes neurological insensibility as total power below 10% of pre-treatment.
That is a meaningful proxy for neural activity, not a direct welfare readout. The electrode/current-path concern remains reasonable for external validity, but I would phrase the issue as partial proxies with unclear thresholds/noise floors and weak industrial translation, not as "the signals tell us nothing".
Sources: Weineck et al. 2018 https://www.mdpi.com/2076-2615/8/9/158; Somerville et al. 2026 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6315379
n conclusion, evidence for electrical stunning is extremely limited and we shouldn't feel comfortable recommending anything with confidence.
GPT5.5-extra: Steelman from the current sources: the evidence does not seem to imply "electrical stunning is bad" or "ice slurry is fine". It implies parameter sensitivity.
The 2026 Somerville et al. preprint reports that lower-voltage/shorter electrical shock followed by cold shock sometimes left substantial neural activity or behavioral response, while higher-voltage/longer shock plus cold shock confirmed insensibility in the no-response group; below-0C ice slurry alone also reduced time to low neural activity. SWP's 2026 review interprets the wider decapod evidence as electrical stunning having greater potential than chilling to induce insensibility, while saying species-specific electrical parameters and operational standards remain uncertain.
Sources: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6315379 and https://www.shrimpwelfareproject.org/humane-stunning-white-paper
We have mixed evidence on whether transitioning egg producers to cage-free improves welfare overall.
GPT5.5-extra: I would narrow this. The record supports "mortality evidence during cage-free transitions is mixed and confounded"; it is less clear that evidence on overall welfare is mixed in the same way.
Schuck-Paim et al. 2021 cover 6,040 flocks and 176M hens and find cage-free aviary mortality falls as producers gain experience, with no recent mortality difference among indoor systems. WFI's welfare model estimates lower cumulative pain in cage-free aviaries than cages, while noting important research gaps. The comment thread also matters: Cynthia Schuck-Paim argues the CSES study is a weak basis for mortality/welfare conclusions because the aviary was poorly managed and not a fair mature-system comparison.
Sources: https://www.nature.com/articles/s41598-021-81868-3 and https://welfarefootprint.org/laying-hens/
We have evidence that the substitution effect of alternative proteins is weak, at best.
GPT5.5-extra: I would soften/generalize this claim. The strongest public evidence I found supports: current plant-based meat and many meat-reduction interventions have weak or uncertain substitution effects.
Peacock's RP report explicitly focuses on plant-based meats because cultivated meats are not widely available; it is not a direct test of future cultivated meat or precision-fermentation products. Green, Smith & Mathur 2025 meta-analyze RCTs of behavior-change interventions and find a very small pooled effect; they also say many promising interventions await rigorous evaluation. That is evidence of a gap and weak current intervention effects, but not yet evidence that all alternative proteins, once genuinely cheaper/tastier/more convenient, would have weak substitution.
Sources: https://rethinkpriorities.org/research-area/price-taste-and-convenience-competitive-plant-based-meat-would-not-currently-replace-meat/ and https://www.sciencedirect.com/science/article/pii/S0195666325003861
GPT5.5-extra: I added a small evidence-audit pass on this post. The detailed notes are threaded under David Reinstein's Hypothes.is annotations, but the main takeaways are:
Shrimp stunning: the evidence seems parameter-sensitive, not a blanket case that electrical stunning is bad or that ice slurry is fine. Current Whiteleg-shrimp evidence supports more R&D and machine validation rather than confident deployment standards.
Tail flips in ice slurry: Weineck et al. 2018 suggests this behavior can be a ventral-nerve-cord reflex, so tail flips alone are a weak proxy for either conscious distress or insensibility.
Electrode and neural/heart signals: the measurements are meaningful proxies, but not direct welfare readouts. Instrumentation, thresholds, and industrial translation remain important uncertainties.
Cage-free hens: the strongest narrower claim is that mortality evidence during cage-free transitions is mixed and confounded. That should not be collapsed into a claim that overall cage-free welfare evidence is equally mixed.
Alternative proteins: the public evidence I found supports weak or uncertain current plant-based substitution effects, but does not directly settle future cultivated meat, precision-fermentation, or genuinely cheaper/tastier/more convenient alternatives.
Detailed threaded notes: - Tail-flip reflex: https://hypothes.is/a/hyqLCmP9EfG-yj97z6fOYA - Electrode/proxy clarification: https://hypothes.is/a/jBrRpmP9EfGf93sIx5Tvwg - Shrimp-stunning evidence: https://hypothes.is/a/kSFQ5GP9EfGIt0f_B-4m3g - Cage-free welfare distinction: https://hypothes.is/a/lhR3FmP9EfGfBDupz9xTgw - Alternative-protein substitution scope: https://hypothes.is/a/nFLdSGP9EfGlirtHBhD0AQ
Layer 1 · The paper
this is a 'layer', yes, and that's relevant for thinking about now, but in the ultimate display I don't think we should call it a 'layer'
The paper's findings bear directly on whether scanner-data demand estimates can be trusted for policy analysis — including animal-welfare-motivated policies that hinge on meat / plant-based substitution elasticities. If observational methods systematically differ from true experimental estimates, cost-effectiveness conclusions built on scanner-data elasticities could be unreliable.
OK your language is good, but why not use direct quotes from evaluation manager's report/summary
Note on the title: The published evaluation summary uses the title "cannot reproduce." The authors subsequently softened the paper title to "does not reproduce" to better reflect the scope of the evidence.
some things like this could should be tooltips
This paper tests whether standard observational demand estimation with rich scanner data recovers the price elasticities revealed by a randomized pricing experiment — and finds they diverge substantially.
link the paper and provide DOI, bibliometrtics etc -- OK, you do that below, but the paper link should really be at the top too.
2 toward more
2 what? What units? This seems a bit of an AI lack of contexgtual understanding
Using data from a large grocery retailer's pricing experiment, Bray, Sanders & Stamatopoulos (Robert Bray, Robert Evan Sanders, and Ioannis Stamatopoulos) ask whether standard observational demand-estimation methods — applied to rich scanner data — recover the "true" price elasticities revealed by a randomized price experiment. They find the answer is no. The observational methods shift own-price elasticities substantially relative to the experimental benchmark:
this is an AI generated summary. Not sure we want that. Perhaps better to lead with content from the Evaluation Manager's summary ... .although I admit this overview seems very useful, as long as it's accurate
The Unjournal · Evaluation package Observational Price Variation in Scanner Data Does Not Reproduce Experimental Price Elasticities
bit at the top a bit too persistent. I can't seem to fold or dissapear it as I scroll down
separate PubPub pages,
and whether having both would be too disagregated/cluttery
Roemheld: The paper documents a striking divergence, but the experimental estimates face a plausibility challenge — they imply profit opportunities far exceeding observed industry margins. Contribution is valuable, but headline conclusion requires stronger foundations.
make it clear when things are quotes vs AI-generated paraphrases
void hosting papers unless there is a clear reason; SSRN, journal sites, institutional repositories, and author pages can remain the paper source. Allow papers to be curated by our team, partner organizations, workshops, funders, or external nominators, not only submitted by authors.
these are not legal-specific -- we do this in the standard model too
Early prioritization prototype
Should be labeled as an early automated prioritization tool, outside of legal research.
high-impact research-candidates workflow
--> 'prioritization workflow'
safety
and governance
nominated
curated by our team or ...
Working papers, workshop drafts, and preprints could benefit from fast structured feedback before journal placement, policy uptake, or citation in public debate.
This is sort of generic -- why is this especially relevant to legal scholarship?
, and improve it.
remove 'and improve it' because the 'it' here is vague. The idea is to help us improve this curation and it's usefulness. We should also invite experts and practitioners to suggest additional research.
legal research
tooltip -- use context to add a note on the prevalence of preprinting/working papers in legal scholarship
or open the direct annotation view.
not sure what this is, but it yields "Access to Via is now restricted This Via link displayed annotations on this page: https://info.unjournal.org/legal-scholarship.html
You can view annotations on this site and others using our Chrome extension, our Bookmarklet, and on sites that embed Hypothesis."
Claude: Deep-research update (June 2026) — new sources added on omnivore fraction of PBM consumers.
Three high-confidence new findings integrated:
GFI US Consumer Snapshot (Jan 2025, Morning Consult Dec 2024, n=3,079): 72% of past-year US PBM eaters are active meat-eaters (57% omnivore + 15% carnivore); only 11% veg*n/pescatarian. Retail panel corroboration: 87% of US retail PBM dollars come from meat-buying households ($970M of $1,118M, NielsenIQ Homescan 2023). Now shown as primary chart in §04.5, replacing the less-precise Hartman Group range.
Neuhofer & Lusk (2022, Scientific Reports — already at src-29) details added: 85.97% of PBMA-buying households also purchased conventional ground meat; only 2.79% were exclusive PBMA buyers. Peer-reviewed, IRI scanner panel, n=38,966 households — the strongest methodological data point in the set.
Bryant Research UK (July 2023, n=1,000, new src-48): Occasional UK PBM consumers ~67% omnivore (consistent with prior claims). Key nuance: frequent UK PBM buyers split ~1/3 each (omnivores, flexitarians, non-meat-eaters). The ≥50% arithmetic lower bound for weekly consumers still holds regardless of frequency segmentation, but the 70–80%+ claim is better supported for occasional buyers or all-buyers combined than for the most committed frequent buyers specifically. This caveat is now added to the §04.5 evidence table and §08.
Stat card updated: '≥50%' replaced by '72%' (US direct survey) as the headline figure, with UK lower bound in the tooltip. TLDR and §08 paragraphs updated accordingly.
Product label + independent confirmation from: Food Navigator, Bloomberg Intelligence, SPINS/NielsenIQ, or academic publication
these should be checked -- this is AI suggestions
pre-registered study is published
pre-reg is no guarrantee of credibility
SV inventories,
But we do want some database structure for the content.
Give both tools the same one-hour task: create a sample template_map.csv from three approved, non-confidential documents and produce a lawyer-readable Markdown summary. Compare setup friction, edit quality, citations to source files, and how easy it is to resume the work later.
this seems like a good test
Unjournal Pivotal Questions — Annotate this page via Hypothes.is (select any text to comment). This working note assesses whether current PBM market evidence is informative enough to study substitution and welfare impact — input to the workshop's research-value question. Produced by David Reinstein with iterative AI prompts.
make it clearer that this is a living document, under active adjustment, and responsive to suggestions
hicken, shrimp, fish, beef, pork, eggs — since welfare weights differ sharply across them
link or tooltip support for this, for people not familiar with welfare weights etc
(c) which animal types bear that displacement and in what proportions,
Put the 'which animal products, and their welfare burden' as the fourth item (d instead of c), because that weighting acts on 'the net reduction in production of each animal product'
supply
I'd make (c) 'how much the production of each animal product adjusts in response in market equilibrium' [tooltip: this may not be 1 for 1, e.g., with scarcity or increasing marginal costs, if some consumers purchase less of an animal product, other consumers may pick up the slack. For example, with an ~inelastic supply of wild fish, if some consumers switch to plant-based equivalents, this may drive prices down, getting other consumers to buy more wild fish]
make it the most tractable
"make it a relatively tractable" ('most' is too conclusive)
plant-based
how large is the plant-based meat market today
This is a relatively lenient threshold (a product can be marginally worse for the median consumer and still cross it
I don't see how this follows -- if 50%+ rate it as as good or better than the conventional product, that should imply that the median consumer finds it 'as good or better'. Correct?
Market-share premium: categories with better average taste vs. worse-tasting categories²⁴ 10× more market share
This wotks better as a note than a quantitative report. Same for "Most favorable public category result" -- perhaps put those at the bottom in a few sentences rather than a tabular format
Net assessment
Fold this ... it's just your own speculation. Maybe even shorten it and use tooltips more, and note it's AI's speculation
The strongest indicator for self-consumption is the lapsed-buyer taste data:
I don't think this is 'the strongest evidence'. To me the GFI Germany/UK surveys seems particular strong at least for the EU.
Survey wording
which survey? a US-one right? THe GFI Europe one asked about actual consumption it seems
consuming
highlight/flag more that this is consuming not just buying
Price evidence
This is missing a lot of studies that look at real-world price data and are even considering plausibly exogenous price shifters -- see https://coda.io/d/Unjournal-Public-Pages_ddIEzDONWdb/Pivotal-Qs-curated-research-list_suEdljp5#_lu4-mRYw for a relevant list and classification of some of these
How to read the evidence for the Pivotal Question
This should be a folding box folded by default, but also I'm not sure these explanations are particularly helpful here.
This supports price as a live lever, but it is not a field elasticity estimate.
This last sentence doesn't add value. Cut it.
finds
"Finds" is too strong ... Weaken this to something like "provides evidence suggesting"
his is about the information content of share data — not an argument against studying displacement rates directly through scanner panels or field experiments
I don't think this sentence is necessary. It's deeply confusing as well. You should probably remove this.
he retail market-share, consumer-panel, and taste-comparability data compiled here give partial evidence on term (a). They give weak or no direct evidence on (b), (c), or (d).
I don't think I agree with this. I don't see how retail market share or taste comparability data tell you about the impact of interventions on plant-based consumption, for example. . Maybe leave these last two sentences out. Or put them in a very speculative tool tip.
but price is the most studied and arguably the most tractable intervention
I'm not sure that either of these things are true. Cut the last part of the sentence, maybe. We're focusing on price because it's something economists are familiar with studying, and there potentially is actual data and variation in prices. (And also, we try to focus on one thing at a time rather than an overwhelmingly large set of questions. )
d the consumer surveys that establish omnivore dominance do not ask whether the purchase was for the respondent's own
However, we've reported on this -- doublecheck it and rethink/revise
In Germany and the UK, the consumer survey story is also broader than a vegn niche. GFI Europe’s late-2024 survey found that 47% of German adults and 41% of UK adults said they were already reducing meat or following a meatless diet, and that 60% in Germany and 56% in the UK reported at least monthly consumption of some plant-based product category. For plant-based meat specifically, 25% of Germans and 23% of Brits reported consuming it in the last month. [DR: That’s an interesting and high level! Consuming (eating?) or just buying it? – digging in here – https://gfieurope.org/wp-content/uploads/2025/05/UK-Understanding-plant-based-category-dynamics-motivations-and-consumers.pdf it seems like we are talking about omnivores actually consuming PBM (regularly), which is important for our question about ‘is it mostly vegns eating PBM’? ] That supports a “mainstream-adjacent but imperfectly integrated” story much better than either a niche-vegan story or a full-substitution story. [13]
within
I'd change the order of the channels. Start with the taste parity, then the PBM buyers mostly being omnivores, and finally, the greater penetration in the natural/specialty channel as well as for some particular products like breakfast patties (the "greater penetration in some products and channels" can be bundled together as point three).
Core finding
Might want to skip this "core finding" altogether and let the evidence below speak for itself.
the natural channel reaches ~8%
Tooltip should explain what "the natural channel" means more carefully here. It's vague to a reader.
The welfare mapping is unresolved
this is a complication but not an insurmountable barrier. Some products are indeed individually distinguished in the relevant data.
It does not prove future price/quality interventions fai
so?
Household-panel evidence weakens a clean substitution story.
Again, this is not a case against trying to measure the displacement/substitution rates!
Market share is at best a ceiling on displacement.
this is true but it doesn't justify "not studying discplacement through scanner data, experiments, etc." The market share we're looking at here is meant to help us understand how plausible it is that substitution patterns currently matter.
Foodservice data prevents an overly retail-only view
I don't see how this supports the claim at the top of the section.
Rügenwalder's reported category role,
tooltip elaborate on this argument
is hypothesis-generating
--> "provides some insights"
ta is informative
"... and more research would have practical value"
nd mostly about ground products.
"observational, not clearly causal, and specific to a particular context".
. The most direct evidence
"arguably" -- this seems too definitive
low
"of high or low"
current public data gives partial evidence
which data? this is vague
displacement ratio × displaced animal mix
This 'X' is not quite clear ... it would have to be some sort of vector multiplication or summed multiplication for the 'mix' part
Context; not direct share data
this subheader is unclear
Consumer surveys and purchase panels consistently show that the large majority of PBM buyers are omnivores or flexitarians who also purchase conventional meat. The category is not, and has never been, predominantly a vegetarian market.
Dig in on this more carefully -- are we sure these are 1. 'regular PBM buyers?' and 2. They are not just buying it for veg*n friends and relatives ?
households would have bought on the specific PB occasions.
"Would have bought otherwise, over the relevant period". Note that displacement need not occur in the exact same shopping trip. Intertemporal concerns could cut both ways. E.g., the 'within-trip substitution' would overstate the total substitution if people commpensate for having purchased PBM on one trip with "now let's eat more real meat" on the next trip or in a restaurant.
Rough conventional meat + aquatic-animal food flow, before a retail price conversion³¹³²
Do the rough price conversion, and also give the 'food flow' for the PBA -- we need a like-for-like comparison
or an added eating occasion?
maybe not 'added eating occasion' but 'simply increased total consumption'.
No public source here gives a like-for-like global conventional retail denominator. A rough calibration is still possible: 365 Mt of global meat plus roughly 165 Mt of aquatic animals used for direct human consumption implies about 530 Mt of conventional animal-product flow before retail conversion. At illustrative retail-equivalent prices of $3, $5, and $8/kg, the denominator would be about $1.6T, $2.7T, and $4.2T, making the $6.6B PB meat/seafood category roughly 0.4%, 0.25%, or 0.16% of that broad scale. This is not a matched market-share estimate.
make this estimate a bit more prominent
s where most of the value and animal-suffering of conventional meat sits,
Can you provide a source for 'where most of the animal-suffering of conventional meat sits'? E.g., what share of chicken consumption is 'whole cut'? What share is on-bone? What about shrimp consumption globally -- whole vs ground up/paste.
Current PB buyers are mostly dual-buyers, not substituters. GFI/SPINS data shows 96% of US plant-based meat buyer households also buy conventional meat, and they buy conventional meat far more frequently. Plant-based meat is functioning as an addition to existing diets in most cases, not a replacement. This complicates the welfare arithmetic: each dollar of PB sold may displace much less than a dollar of conventional.
See previous discussion. This actually makes it MORE interesting to study, and offers more potential for displacement, the case in which it seemed that only prior vegetarians were buying this stuff
Trajectories from current data may be misleading for projecting future adoption with better products.
this doesn't seem to follow from the previous sentence
Quality at parity hasn't unlocked majority adoption. Plant-based nuggets — the format that has reached sensory parity in blinded testing — still hold only 2 to 3% of the conventional nugget category. If matching taste isn't sufficient, then taste investments alone may have lower returns than the parity-headroom argument suggests.
Think about this more and state in a a more reasoned logical way. Note that we're largely thinking about price here (as well as taste, nutrition and availability). We're largely focused on the the impact of cost and price on consumption and substitution. In fact, skeptics were saying that "we don't care too much about substitution and price impacts because 1. it has such a low market share and 2. it's not taste or nutrition comparable."
Foodservice growth is real where products work. EU plant-based burger servings grew 90% from 2019 to 2023 in the Big 5 according to Circana. In channels where the product fits the use case and the price gap is hidden in menu pricing, adoption looks very different from retail. This is itself a quality-of-format finding.
Looks like circular reasoning here. I'm not sure that this 'finding' is meaningful. It might need rephrasing
because most PB buyers are dual-buyers, but the category is not literally too small to matter.
At the end, it doesn't quite make sense. If all PBM buyers (or consumers) were previously vegetarians, then the displacement would be close to zero. If they all only ate meat or PBM and consumed the exact same amount of protein every day, the displacement would be 100%. So it's not the 'dual buyers' that makes displacement less than 100% per se. The question is to what extent consumers, whether vegetarians or omnivores, are buying PBM 'instead of meat' or 'instead of other vegetarian/vegan food'.
material
evidence that taste is one binding constraint.
I'd say "evidence suggesting that it may be a binding constraint" ... people may report one thing, but actually something else could be fundamentally behind their decision, perhaps even something ~subliminal that they can't identify themselves.
A frank attempt to engage rather than defer.
skip this sentence
NECTAR 2024 sensory study: category-level parity with conventional²⁰ Nuggets only
An important fact, but a little bit strange to mix in here. It really belongs in the section below. ... tit's not quantitative either
closest international analogu
? Have you really checked all other countries? Are you saying the US is a leader as well as Germany? That doesn't comport with my casual empiricism.
but the cleanest topline is not the 6 to 7% US patty figure; it is the combination of low overall share with selective format-level strength and partial taste parity.
skip This last bit, it's tpo AI, "not this but that" and the patties are a distraction.
Consider whether this is really overlapping the bit in italics just after the title.
Public format-level summaries suggest much higher penetration in a few reformed categorie
"reformed categories" Is not clear here. Give an example number (other than patties)
Germany at 3.1% with similar product quality to the US's 1.4% shows that non-product factors (sausage culture, retailer strategy, private-label investment)
"Shows" It is too strong. Maybe quotes suggest, but even then you're not really providing transparent reasoning here.
If treated as approximately 1:1 substitution
That's a big if - we need evidence. That is presumably the ceiling on the substitution.
Roughly 9% of US households tried plant-based meat and stopped.
That's just a simple subtraction of 20% -11%? Because it's also possible that more than 9% stopped but some new users entered.
bratwurst
Are you sure about bratwurst? What's your source for this?
NECTAR sensory study: PB formats reaching parity with conventional²⁰
This is high value. Put something about this in the overview.
n the US it reaches 6 to 7% of conventional packaged patty dollar sales². The category-average understates penetration in the formats where taste and texture gaps are smallest, but the patty figure is itself an overstatement of plant-based meat's share of all hamburger consumption (see caveat below).
Leave the 'patty' figure out -- put that whole discussion in a tooltip. Add back some numbers about EU or German share of some other relevant categories like sausage (or what's the highest penetration category other than patties?)
The sceptical concerns are partially but not fully supported. Overall share is genuinely low (US retail: 1.4%; Germany: 3.1%) and most products lag on taste. But three patterns make the evidence more informative than a simple dismissal implies: within the US, channel-level penetration varies widely — natural/specialty retailers such as Whole Foods reach ~8% of packaged-meat dollars vs 1.4% in mainstream multi-outlet retail; most buyers are omnivores or flexitarians rather than prior veg*ns, though whether they buy for their own consumption or as proxy for a veg*n household member remains open (§04.5); and better-tasting product categories capture 10× more market share, suggesting taste improvements have measurable adoption effects. Whether these patterns extrapolate to higher-quality, larger-market conditions is the central unresolved question.
Most of this is given in the 'a quick take' below. Just make this 2 sentences and flag 'unfold below for a quick take on the evidence'. And incorporate " better-tasting product categories capture 10× more market share, " with the reference tooltip into the fold below. -- Everything else here is basically already covered in that fold!
versus 1.4% in mainstream multi-outlet.
wait -- 1.4% is also the OVERALL -- are you sure 1.4% is 'mainstream"? The natural organic channel is virtually none of the market!
A quick take: The sceptical concerns are only partially supported
make it folded by default. And avoid overlap with the above
raised
surfaced
1
footnote s should hyperlink back to their place in the text
Each footnote in the dashboard links to a numbered row here. The full quote (or specific evidence) is shown in italics. URLs are direct links to the cited page or PDF where available.
some numbers are missing -- e.g., where is 36-39?
here someone has published
"where someone has published" -- this language is a bit too informal and amateurish. Improve it ... something like "where we could find a published cross-tabulation..."
, products in better-tasting categories already c
I'd make the third point the evidence that there's evidence of taste parity for some products.
giving enough structural variation to analyse what drives adoption.
remove this claim. That's subjective
hese are genuinely low figures
this line is meaningless. Delete this sentence. People can interpret the numbers as they wish
The
Header for this: "A quick take: The sceptical concerns are only partially supported" ... and make this a folding box
The key open question is whether these patterns extrapolate to better-quality conditions.
skip this lat line
in formats, channels, and geographies to study?
not sure we need this type of variation .. more like 'is there sufficient available relevant data to permit meaningful statistical analysis.
Workshop
--> Pre-workshop discussion
r: how much do plant-based products actually replace animal products? This is the focus of The Unjournal's Plant-Based Substitution Pivotal Question.
We are expanding this focus a bit for the workshop to consider substitution issues more generally, and perhaps more.
Background note: a first-pass Claude summary of evidence on PBA penetration and taste-comparability is available for sharing. It is exploratory rather than a vetted literature review.
"Background: Is the PBA market mature enough for substitution measures to matter" -- make that the italiicized header for this but
ROI and Research Gaps (~20 min) — Is PBA funding competitive with corporate campaigns given current evidence? What research would most reduce uncertainty?
This is only going to work if we have people involved with animal welfare funding and modeling it on board
rticipants share updated beliefs
Belief elicitation and updating probably cannot occur in real time. Too much thinking is needed. As in, the previous workshops will encourage people to submit their beliefs before the workshop, and then talk them through it during the workshop, and then ask them to submit their beliefs after the workshop. Finally, share what others thought and ask them to update their beliefs.
operationalized PBA pivotal questions; p
Link this instead: https://uj-pba-workshop.netlify.app/beliefs
live discussion of disagreements
We're probably going to need to structure this live discussion. It's not clear what an organic discussion of this would look like. Do we have specific computing models? Will people be citing certain papers? Will it just be vibes?
Also don't use the word "disagreements" here?
credibility and limitations of each
I don't think you need this bit at the end. I think that's kind of obvious. Instead, we could frame it in terms of ~'which approaches are (more) reliable for the practical questions?'
Methods Debate (~30 min) — Structured exchange between demand-estimation approaches and experimental/survey approaches; credibility and limitations of each
This should be longer if we get participation from researchers in this area.
funders
Rephrase this: Why do animal welfare advocates and funders care about substitution?
he empirical finding that most PBA purchasers are omnivores;
This is stated too strongly. We don't have this as a finding yet. It was just an initial literature review.
segments
"drop-in segments" -- Make it clear that people can join for only the parts they're interested in.
For Anthony
not just for Anthony
What share of cultured meat companies (those with capex over $10 million) will design and build their own bioreactors by 2036?
Consider: is this more about fit-for-purpose equipment vs. pharma-grade-- the former could also include CM-specific B2B offerings.
Achievable densities in a 20kL bioreactor2420,000L used as reference scale for industrial production in most TEAs. Smaller facilities are R&D-scale. by 2036 (CM_16); binding constraints; and trade-offs in custom-built vs. off-the-shelf bioreactor design25Off-the-shelf: pharma-grade bioreactors, expensive but proven. Custom-built: fabricated to reduce capex (some claim under $1M for 20kL). The choice significantly affects capex in TEAs. Learn: bioreactor types →. Discussion space — unfold & annotate via Hypothes.is
20k L or 10k L?
Other Pivotal Questions Workshops 🥩 Cultivated Meat (Apr 2026) 🥗 Plant-Based Alternatives (May 2026)
PBM workshop probably deferred to June -- update
test
We’ve reviewed this critique carefully
this should be more "we're reviewing it now and so far it seems reliable"
New to this model? Start with the Simplest Model → — a shorter version with only the biggest levers, line-of-sight explanations, and no jargon. You can carry your settings over to this Advanced Model when you’re ready.
skip the 'and no jargon' ... and it's "focusing on some key levers"
Save / share this scenario:
The ability to do this should be a bit more prominent and signposted perhaps at the top and the very bottom as well. Ideally there should be a way to save this and then have a page that gives a side-by-side comparison of the results from two scenarios without extra clutter ... This would be particularly useful if it's something that's easy to develop.
For now you can explain (tooltip) how you could do something like this by copying two shareable links and looking them in side-by-side browsers, or saving the results somewhere and feeding it into an LLM to ask it to give a comparative analysis
Earlier versions of this model carried a separate
Make it clearer here initially that these micronutrients seems to be only a tiny cost, anyways.
Also you don't need to make the quote "April 2026" change part of the header - perhaps just make that a note or a tooltip. This is too much discussion of our process
All costs in this model are expressed
Expressed in the equations and initial computation that is -- on the dashboard, you can see the adjusted
he CDMO toll is sampled from a lognormal distribution (default p5 = $4/kg, p95 = $40/kg) representing the range of per-kg fees a future food-grade contract manufacturer might charge. See the CDMO mode section below for a full description.
Is it reasonable to think of the CDMO total as being per kilogram? Or is that just the result of other computations? Look for references in discussion about this to verify
VOC · CAPEX · F
These tool tips are not showing any content when you hover over them
Return to: Interactive Cost Model | New to this topic? How Cultured Chicken is Made | Audio Review (MP3) | Workshop (May 2026)
Let's update the audio review with new content
Cell Density / Media-Use Override Code viewof override_mode_constraints = Inputs.toggle({ label: html`Override process mode constraints <abbr style="cursor:help;text-decoration:underline dotted;font-size:0.85em;color:#888;" title="When ON: process-mode sampling is bypassed and you can specify density and media-use ranges directly. Useful for experts wanting to model specific bioreactor configurations.">(?)</abbr>`, value: urlBool("override_mode_constraints", false) }) Override process mode constraints (?)override_mode_constraints = false Code viewof density_lo = Inputs.range([10, 100], { value: urlNum("density_lo", 30), step: 10, label: "Cell Density Low (g/L)" }) viewof density_hi = Inputs.range([50, 300], { value: urlNum("density_hi", 200), step: 10, label: "Cell Density High (g/L)" }) Cell Density Low (g/L) density_lo = 30 Cell Density High (g/L) density_hi = 200 What is cell density and why does it matter so much? (click to expand) Cell density (g/L at harvest) determines how much meat you get per liter of bioreactor volume. Higher density means less media per kilogram of product, which directly reduces the largest variable cost. Density Media per kg Typical context 10 g/L ~100 L/kg Current lab scale 50 g/L ~20 L/kg Near-term commercial target 200 g/L ~5 L/kg Optimistic TEA projection This is multiplicative. If media costs $1/L, going from 10 to 50 g/L cuts media cost from $100/kg to $20/kg. Going to 200 g/L cuts it to $5/kg. Cell density is arguably the single most important technical parameter for cost reduction. Current state: Most published data shows 10-50 g/L. Some companies claim higher, but these claims are difficult to verify independently. Lever VC’s 2025 report claims 60-90 g/L has been achieved by “second generation” companies. Whether 200 g/L is achievable by 2036 is a genuine open question. What about bioreactor volume / tank size? (click to expand) Bioreactor volume is another major uncertainty that is currently implicit in this model rather than a direct parameter. The model computes total working volume as: total_volume = annual_output / (density × productivity × 365). It then applies a power-law scaling for CAPEX. But individual bioreactor tank size matters for several reasons: Factor Small tanks (2,000-5,000L) Large tanks (20,000-50,000L) Cost per liter Higher Lower (economies of scale) Contamination risk Lower Higher (single failure = large loss) Mixing/O2 transfer Easier Harder at scale Flexibility More modular Less redundancy Industry precedent Pharma standard Requires new engineering Key debate: Some companies (e.g., Vow) claim to have built 20,000L bioreactors for under $1M in 14 weeks using custom food-grade designs. If true, this dramatically changes the CAPEX picture. Humbird’s analysis assumed pharma-grade bioreactors at $50-500/L. Why it’s not a direct slider (yet): Adding individual tank size would require modeling the number of tanks, contamination batch-failure rates, and the trade-off between scale and reliability. This is a planned enhancement. For now, the Plant Capacity and Cell Density parameters together determine total working volume, and the custom reactor ratio (in full view) captures the pharma-vs-food-grade cost difference. Workshop discussion: This is one of the key cruxes for the upcoming CM workshop — what bioreactor scale is realistic, and what does it cost? Advanced: Media-use multiplier (×) What is this — and why can it be below 1? (click to expand) The model computes media volume per kg as (1000 / density) × multiplier. A value of 1 is traditional batch mode (fill reactor once, harvest); >1 is perfusion (multiple media-volume equivalents flow through during the run); <1 represents media recycling, fed-batch with concentrated feeds, or harvest-side cell concentration. The Learn page walks through all three mechanisms. Why the range changed (April 2026): the default p5–p95 was tightened from 1–10× to 0.5–3.0×. The old floor of 1.0 was too restrictive — the GFI 2023 cost-competitive scenarios assume 8–13 L/kg, which at 60–90 g/L density implies a multiplier of roughly 0.5–1.2. A floor of 1.0 mechanically excluded those scenarios no matter how high you pushed density. The new range covers both recycled/fed-batch (<1) and standard perfusion (up to ~3×); values of 5–10× remain plausible for heavily media-intensive processes but are now a stress-test region rather than the default. Show multiplier sliders Code viewof media_turnover_lo = Inputs.range([0.25, 2], { value: urlNum("media_turnover_lo", 0.5), step: 0.05, label: "Media-use multiplier p5 (low end)" }) viewof media_turnover_hi = Inputs.range([1, 10], { value: urlNum("media_turnover_hi", 3.0), step: 0.1, label: "Media-use multiplier p95 (high end)" }) Media-use multiplier p5 (low end) media_turnover_lo = 0.5 Media-use multiplier p95 (high end) media_turnover_hi = 3 Code // URL state writer: serialize every viewof value that DIFFERS FROM ITS // DEFAULT into ?key=val pairs, then debounce-write to the URL via // history.replaceState. Critical invariant: if every slider is at its // default, the URL stays bare (pathname + hash only) — no query string. // This is required so Hypothes.is can find annotations on the canonical // bare URL; a polluted URL breaks annotation lookup for every visitor. // The writer depends on every viewof name below so OJS re-runs it // whenever any input changes. Reads nothing from urlParams. { // Hard-coded defaults must stay in sync with each Inputs.range() / // Inputs.toggle() declaration above and with the reset_adoption button. const defaults = { simpleMode: true, include_blending: false, blending_share: 0.25, filler_cost: 3, include_capex: true, include_fixed_opex: true, include_downstream: false, cdmo_mode: false, cdmo_toll_p5: 4, cdmo_toll_p95: 40, bundled_media: false, bundled_media_p5: 50, bundled_media_p95: 500, plant_capacity: 20, uptime: 0.90, maturity: 0.5, target_year: 2036, p_fedbatch: 0.20, p_perfusion: 0.50, p_continuous: 0.30, override_mode_constraints: false, p_hydro: 0.75, p_recfactors: 0.5, gf_progress: 50, wacc_lo: 8, wacc_hi: 20, asset_life_lo: 8, asset_life_hi: 20, density_lo: 30, density_hi: 200, media_turnover_lo: 0.5, media_turnover_hi: 3.0 }; const state = { simpleMode, include_blending, blending_share, filler_cost, include_capex, include_fixed_opex, include_downstream, cdmo_mode, cdmo_toll_p5, cdmo_toll_p95, bundled_media, bundled_media_p5, bundled_media_p95, plant_capacity, uptime, maturity, target_year, p_fedbatch, p_perfusion, p_continuous, override_mode_constraints, p_hydro, p_recfactors, gf_progress, wacc_lo, wacc_hi, asset_life_lo, asset_life_hi, density_lo, density_hi, media_turnover_lo, media_turnover_hi }; const usp = new URLSearchParams(); let hasDiff = false; for (const [k, v] of Object.entries(state)) { const def = defaults[k]; let matches; if (typeof v === "boolean") matches = (v === def); else if (typeof v === "number") matches = Math.abs(v - def) < 1e-9; else matches = (v === def); if (!matches) { hasDiff = true; if (typeof v === "boolean") usp.set(k, v ? "1" : "0"); else if (typeof v === "number" && Number.isFinite(v)) usp.set(k, String(v)); } } if (window._urlWriteTimer) clearTimeout(window._urlWriteTimer); window._urlWriteTimer = setTimeout(() => { try { const newUrl = hasDiff ? (location.pathname + "?" + usp.toString() + location.hash) : (location.pathname + location.hash); history.replaceState(null, "", newUrl); } catch (e) { console.warn("URL state update failed:", e); } }, 300); return null; } null
This bit at the bottom seems to have generated some sort of error. It says "null"
In our sensitivity analysis,
A little bit more cagey about this. I'm not sure this holds in a robust way, not sure we fully checked. Say something like, "In our preliminary sensitivity analysis these seem to contribute less ..."
doption, reactor costs, and financing. High maturity = correlated improvements.
I'm going to link the fuller explanation in the formula and explainers page
→ Open Advanced Model with these settings
I think it's more like "starting with these settings," or "adapting the parameters you've entered here."
How is this cost calculated?
I think we need a bit more explanation here, perhaps even including some unfolded quick points about what kind of model this is, how the uncertainty comes in through simulations, etc., and what we're assuming about correlation or lack thereof between the different elements. We don't want to keep this simple and short but people should have some idea of what exactly they're looking at
Full formula documentation → Model formulas & metrics Code html`<div style="margin-top:1.5rem; padding:0.8rem; background:#f0f8ff; border:1px solid #3498db; border-radius:6px; font-size:0.88em;"> <strong>Want more control?</strong> The <a href="index.html">Advanced Model</a> exposes all parameters: financing (WACC, asset life), plant capacity, cell density, media-use multiplier, CDMO mode, bundled media pricing, and more. <div style="margin-top:0.5rem;"> <a href="${(() => { const cont=Math.max(0,100-p_fedbatch_s-p_perfusion_s); const p=new URLSearchParams({target_year:target_year_s,p_hydro:(p_hydro_s/100).toFixed(2),p_recfactors:(p_recfactors_s/100).toFixed(2),p_fedbatch:(p_fedbatch_s/100).toFixed(2),p_perfusion:(p_perfusion_s/100).toFixed(2),p_continuous:(cont/100).toFixed(2),include_blending:include_blending_s?1:0,blending_share:(blending_share_s/100).toFixed(2)}); return 'index.html?'+p.toString(); })()}" style="font-weight:600;">→ Open Advanced Model with these settings</a> </div> </div>`
I think those formula explanations pertain to the full model. Perhaps it would be better to have this linked directly to a new page or part of the page that just explains this simpler model
Always included
Again, at what rate, and what's the reference for this particular rate? Is it given as a fixed value or a distributional draw?
included
Included, but at what rate/what value? And what's the reference or source for this?
Reference commercial scale
Link, reference, or tooltip it here.
Standard equipment life range
Give a bit more reference for this. I'm actually a bit confused as to which equipment we're talking about. Sourced reference would give more credibility.
8–20% range Typical food/biotech financing range
Explain this more. Are we drawing this from this particular distribution? Make a note or a tool tip about how the results are generally not particularly sensitive to this parameter, given the explanation you gave before, where the capital costs are really a rather small component in this context.
Parameter Value Why fixed Industry Maturity 0.5 (neutral) At 0.5 the maturity factor has zero net effect on probabilities or financing
This explanation is incomplete or it just doesn't make sense. Can you elaborate, and why is this the baseline you think maturity should matter for something?
Probability Thresholds Code { function card(thresh, prob, label, color, bprob) { const bc = prob > 30 ? color : '#ddd'; const blend = include_blending_s && bprob !== undefined ? `<div style="font-size:0.8em; color:#1a5276; background:#f0f8ff; border-radius:3px; padding:2px 5px; margin-top:4px;"> Blended: <strong>${bprob.toFixed(1)}%</strong> chance < $${thresh}/kg </div>` : ''; return `<div style="border:2px solid ${bc}; padding:0.9rem; border-radius:8px; text-align:center;"> <h5 style="margin:0 0 0.2rem;">P(Pure cells < $${thresh}/kg)</h5> <h2 style="color:${color}; margin:0.2rem 0;">${prob.toFixed(1)}%</h2> <small style="color:#666;">${label}</small> ${blend} </div>`; } const grid = `<div class="grid" style="grid-template-columns:repeat(4,1fr); gap:0.75rem; margin-bottom:1.5rem;"> ${card(10, stats_s.prob_10, 'could approach conventional chicken (~$5-10/kg retail)', '#27ae60', stats_s.bprob_10)} ${card(25, stats_s.prob_25, 'range where premium cultured products may be viable', '#3498db', stats_s.bprob_25)} ${card(50, stats_s.prob_50, 'potential niche/specialty market', '#f39c12', null)} ${card(100, stats_s.prob_100, 'substantially below current lab-scale costs', '#e74c3c', null)} </div>`; const blendRow = include_blending_s ? ` <p style="font-size:0.88em; color:#1a5276; font-weight:500; margin:0.5rem 0 0.3rem;"> Blended product (${stats_s.bs*100|0}% CM + ${((1-stats_s.bs)*100)|0}% filler at $3/kg) — consumer-relevant prices: </p> <div class="grid" style="grid-template-columns:repeat(3,1fr); gap:0.6rem; margin-bottom:1.5rem;"> <div style="border:2px solid ${stats_s.bprob_5>20?'#27ae60':'#ddd'}; padding:0.8rem; border-radius:8px; text-align:center;"> <h5 style="font-size:0.85em; margin:0 0 0.2rem;">P(Blend < $5/kg)</h5> <h2 style="color:#27ae60; margin:0.2rem 0;">${stats_s.bprob_5.toFixed(1)}%</h2> <small>competitive with conventional chicken</small> </div> <div style="border:2px solid ${stats_s.bprob_8>30?'#3498db':'#ddd'}; padding:0.8rem; border-radius:8px; text-align:center;"> <h5 style="font-size:0.85em; margin:0 0 0.2rem;">P(Blend < $8/kg)</h5> <h2 style="color:#3498db; margin:0.2rem 0;">${stats_s.bprob_8.toFixed(1)}%</h2> <small>competitive with premium chicken/beef</small> </div> <div style="border:2px solid ${stats_s.bprob_12>50?'#f39c12':'#ddd'}; padding:0.8rem; border-radius:8px; text-align:center;"> <h5 style="font-size:0.85em; margin:0 0 0.2rem;">P(Blend < $12/kg)</h5> <h2 style="color:#f39c12; margin:0.2rem 0;">${stats_s.bprob_12.toFixed(1)}%</h2> <small>affordable specialty market</small> </div> </div>` : ''; return html([grid + blendRow]); } TypeError: Cannot read properties of null (reading 'toFixed')
The probability thresholds yield this error when you select that you want to show blended product.
TypeError: Cannot read properties of null (reading 'toFixed')
I'm getting "TypeError: Cannot read properties of null (reading 'toFixed')" for the probability thresholds here
Blended Product Code viewof include_blending_s = Inputs.toggle({ label: "Show blended product analysis", value: urlBool_s("include_blending", false) })
A bit more signposting here, please. Tooltip, if it will fit nicely. Maybe move this one to the top. And make it selected by default.
all parameters
"all" is too strong - better to say "many more".
Projected 2036 Cost Distribution:where(.plot-d6a7b5) { --plot-background: white; display: block; height: auto; height: intrinsic; max-width: 100%; } :where(.plot-d6a7b5 text), :where(.plot-d6a7b5 tspan) { white-space: pre; }
Make it easier to expand this or zoom in on it, perhaps making it full screen. However, type tool tips within the graph could also be helpful, to be able to see the lower percentiles better. I'm not seeing the P80 here.
A first look at cultured chicken cost — for exploration and understanding
You can leave this out because the caution below gets at it.
Year
Important. Nothing seems to be changing when I change the projection year! I would think that this model allows for technological change, even if they don't explicitly set the equitment maturity parameter"!
Continuous (auto): 35%
Let them set all three, but still have them automatically add up.
These parameters need a lot more explanation.
I think we can use this space better here. If you're only going to be showing a small set of "results" tables (maybe with others in folding boxes), you could just put these below the results, allowing a more fleshed out and spacious explanation of what the parameters mean, rather than this sidebar.
xposes only the biggest levers on cultured chicken
that's potentially too strong a claim. yes, some of the most important levers are here, but we also focused on the ~'simpler' elements requiring less explanation #implement.
I'd say something like "the simplest model lets you adjust some of the more important levers..."
WACC
tooltips to explain this and other things. People may not even know what this abbreviation means.
Background
hyperlink that if possible
Parameters
"Exposed" is weird. Say something more like "Choices and adjustable parameters here"
Mix
"mix" is confusing ... "Probability of each process mode" is more accurate
·
commas, not dots (dots look like multiplication)
For more complete analysis with all parameters exposed
That one also has caveats and is not fully ready for prime time ... rephrase this
38.7% chance blended product (25% CM, $3/kg filler) < $10/kg
This is basically also given in the boxes below, but with slightly different thresholds, which is confusing.We only need one or the other, as far as I understand it. Simplify (if this is also the case in the intermediate sluttage advanced model, fix it there too. )