1,586 Matching Annotations
  1. Last 7 days
    1. We are looking for a credible legal-scholarship lead or close partner who can help adapt the model and decide whether a small pilot is worth running.

      more like 'help us run a small pilot'. We're also looking for feedback from legal scholars and users of this research ... also loose commitments to be part of an advisory board if this moves forward.

    1. how quickly alternatives to animal-source foods must diffuse for the food system to make a meaningful contribution to climate targets. That is directly relevant to public R&D, procurement, regulation, investment, and philanthropic choices being made by organizations working on climate mitigation, food systems, and animal welfare.

      relevant yes. But how do we know it's important for these questions?

    1. PQ1A: What is your probability that linear WELLBY comparisons are reliable enough for comparing interventions in LMICs? Respondents gave a central estimate (0–100%) and a 90% credible interval.

      Note -- I did not intent to have CIs over probabilities. This was an artifact of a changed question and vibe coding. Also investigate whether this was the wording of the question when participants answered it

    Annotators

  2. May 2026
    1. Germany consumer survey · late 2024 Free GFI Europe consumer survey (late 2024, published 2025): 25% of German adults and 23% of UK adults reported consuming plant-based meat in the last month. 47% of German adults and 41% of UK adults reported already reducing their meat intake or following a meatless diet. 60% in Germany and 56% in the UK reported at least monthly consumption of some plant-based product category (broader than meat). Since only ~5% of German consumers exclusively consume alternative proteins (see src-35), the large majority of the 25% monthly PBM consumers are omnivores. Survey-reported personal consumption is more direct evidence of self-eating than purchase-panel data, which tracks household-level transactions without identifying wh

      this seems to need more digging into!

    2. Together: PBM is roughly 0.1–0.15% of conventional by volume, or 0.16–0.4% by illustrative retail valu

      this seems worth highlighting, even if it's a rough calculation

    1. 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.

      shorten this a bit

    2. plant-based burgers are mostly substituting away from beef (not chicken),

      The lower animal welfare burden of beef vs chicken may not be known to all readers

    3. Connect to decisions: Given current evidence, is PBA funding plausibly competitive with corporate campaigns?

      Also mention other questions, such as "will meat taxes improve or worsen animal welfare?" and "Will innovative products such as PBA and cultured meat substitute for farmed animal consumption, or will they mainly be taken up by (existing) vegans and vegetarians"

    4. Quantify uncertainty: What's a reasonable range for the cross-price elasticity between PBAs and chicken, given what we know and don't know?

      This is kind of captured above, but I would do something more here with belief elicitation, interactive updating, and aggregating knowledge.

    5. nd can we conclude anything at all with current methods?

      Rather than "conclude" something like "do currently available methods and data even yield useful insight?"

    6. can we actually conclude about substitution effect

      Conclude is too strong here. I would say, what can we reasonably say about substitution effects and with what confidence?

    7. identification strategies vary considerably in rigor.

      Mention the use of instrumental variables and other strategies here, perhaps in a tooltip. Give specific references in that tooltip.

    8. raising questions about which to trust.

      Add a tooltip here, discussing some of the strengths and limitations of each, using the context and explanations discussed elsewhere . Let me know if you need more context on this.

    9. Different specifications can yield very different elasticity estimates.

      ... (tooltip) Note this is in part due to the aforemationed point that elasticity is not likely to be constant across an individual or market demand curve, and there will also be heterogeneity thus, it matters what parts of the curve you are looking at, and which markets, times, etc.

    10. IV and experimental estimates often diverge in opposite directions from naive OLS.

      rephrase this -- it's not quite right, and confusing

      Also be clear: these are estimates of own price elasticity, although it seems unlikely that cross-price elasticities would be more consistent or robust. And these are price-shifting field experiments. But also note, in a tooltip, some of the critiques of these experiments themselves. Ask me if you need context.

    11. especially in the earlier years when these products were emerging.

      I don't see what this part of the sentence adds. If the data is available in later years, we can focus on that later data. Maybe just leave this out, or mention something like "partly because of the limited availability of these products, and lags in releasing data for research use." -- But That's tooltip details. Also, I want you to ground some of these statements with references and links, mainly in tooltips.

    12. they anticipate lower demand,

      More when they expect demand to be more price sensitive --- have pro or counter-cyclical pricing; Put the details in a tooltip

    13. Why this is hard to measure

      These explanations are taking up too much space and will take up even more when you consider a wider range of approaches.

      Use folding boxes and tooltips more.

    14. everal key challenges complicate this:

      These are key issues with ~traditional econometric (IO and quant. marketing) methods.

      Field experiments (supermarket-level or at school cafeterias etc.) have less of an endogeneity issue, but some of these issues are still present (e.g., short term vs long term), and these are hard to implement at scale and cleanly, and have issues of their own (see the notes/discussion, and sketch these).

      Hypothetical and small-value choice experiments and hypothetical discrete choice surveys have other important limitations (mention these, from the sources and discussion).

    15. the strongest causal evidence.

      moderate this. This is vague. and there are a few kinds of field experiments in addition to this, including price shift experiments (esp. Bray et al), although few if any involving PBA

    16. These measurement challenges mean we should interpret existing estimates cautiously, while still extracting what information we can. The workshop will discuss which methods are most trustworthy and what further research could help.

      this is a bit generic, maybe not necessary

    17. One concrete finding worth engaging: The evidence suggests that the vast majority of PBA purchasers are omnivores, not vegetarians or vegans — one study finds that only around 1% of high-spending plant-based meat alternative households are actually vegetarian. This challenges the intuition that "PBA just captures existing vegans" and raises the stakes for substitution estimation: the counterfactual meat consumption displaced may be much larger than assumed.

      This is probly too strong ... needs caveating and referencing and tooltips.

    18. (chicken vs. beef vs. pork),

      make this 'between different animal products' and 'e.g., chicken vs. beef vs. eggs...' -- relevant for AW when considering issues like the AW impact of meat taxes -- which might shift consumption from beef to chicken, with a higher AW burden -- mention this briefly with further details in a tooltip

    1. US plant-based beef price premium vs conventional beef, category average

      Research and state this. Also for impossible and. Beyond vs conventionally ground beef

    2. Butcher) and the Nordic countries, where per-capita consumption of plant-based foods is high — probably sit above Germany, whic

      Evidence for this claim? Otw State as ,,we. SpeculTE that,,

    1. David Manheim (Technion/ALTER) and Mirjam Capuder (University of Maribor) participated. The session was recorded — all attendees joined knowing this. It covered introductions, a walkthrough of the interactive cost model dashboard, and early framing questions about key modeling uncertainties. Full recording pending participant review before public release.

      mention the insights here? I'm not sure we'll put out htis video either; it's not something interesting to watch , I guess. It was mostly preparation and broad discussion.

    2. ene-edited cell lines are the most under-modeled factor in published TEAs.

      this is a strong claim ("most under-modeled") -- what's it based on? Reasoning transparency please. Provide support and links to this, tooltips etc. I want to make sure this is well-backed before I post and ~"co-sign" it !

    3. technology and reaching different conclusions based on different priors about scale-up timelines and capital availability.

      all claims need more direct supporting evidence ... quotes, links, etc.; tooltips are your friend

    4. 1. The $1–$100/kg spread is real disagreement, not just uncertainty. Named domain experts — Swartz ($25/kg) and Lattanzi ($100/kg) — are 4× apart with tight confidence intervals. This isn't a calibration problem; they're looking at the same technology and reaching different conclusions based on different priors about scale-up timelines and capital availability.

      wait -- are you sharing the beliefs here? we didn't wnt to do that yet!

    5. European Morning Drop-in Fri May 8, 2026 · 9:00–10:00am ET (3–4pm UK · 4–5pm CET) · Zoom Informal drop-in for EU/UK participants who could not stay for the full afternoon session. Primarily attended by European/UK participants (CET timezone). The session was a recorded Zoom — all attendees joined knowing this. It covered introductions and a preview of the hydrolysates and gene editing framing that would open S1. Full recording pending participant review before public release.

      skip/remove this -- no one showed up

    6. while Believer Meats — the company behind the optimistic Pasitka TEA — closed in December 2025.

      you keep pushing this -- it's ok to mention but the way it's written it seems like you are calling them out for hypocrisy; too harsh, and there can be other explanations

    1. Research and evaluation priorities — Which specific papers, issues, or research questions should The Unjournal prioritize for expert evaluation as part of the CM cost viability Pivotal Question? What new research (e.g., TEA reviews, production cost benchmarks, expert elicitation)92For context on what's already been identified: see the workshop reading list → and the UJ CM research scoping on Coda → or data would most reduce remaining uncertainty? [pre-session note]93David Manheim (Technion/ALTER, participated in May 6 pre-session) suggested we also consider: AI-powered and robotics-driven advances in manufacturing and bioengineering that may spill over from other fields, and scenarios where non-chicken species (salmon, veal) become the viable CM product first. [Suggested discussants]Suggested discussants:Matt McNulty (Tufts CCA) — strategic view of research priorities from an academic CM centerElliot Swartz (GFI) — has systematically mapped CM research gaps; knows what evidence would most shift the cost pictureJakub Kozlowski (model developer) — knows where the model's input uncertainties are largest; can specify what data would most tighten them

      Eliot: Feed conversion ratio, taste studies on inclusion rates, actual cost of equipment, capital needs; scale out or up?

      "We know more about media costs already"

    2. What would commercially viable CM production actually require; on what horizon; and what does industry experience suggest about the factors beyond production cost that determine whether a CM business can sustain itself? Price parity63Parity could be with conventional meat, a hybrid product (cells + plant-based inputs), or a niche premium product. The relevant cost target differs significantly between these cases. is not the only route; hybrid products, niche markets, or differentiated positioning64Consumer acceptance, regulatory pathways, and market positioning are important questions that may be covered in other workshops or projects. But these routes to viability are relevant context for understanding what cost targets need to be reached. are also paths. Discussion space — unfold & annotate via Hypothes.isPaths to commercial viability — discussion spaceUse #question to flag something for verbal discussion during the session.Requirements for viability by 2036 [?]65What needs to be true — technically, financially, or politically — for CM to reach viability by 2036?Hybrid/niche paths [?]66Are hybrid products or niche markets a more realistic near-term path than full cost parity with conventional meat?Lessons from company challenges [?]67What do recent company difficulties teach us about what viability requires beyond production cost; including return on R&D investment?Other (S2 viability) — annotate here to add a point not covered aboveQuestions for discussants — annotate here to surface your question during the session[how this works]68Annotate this page via the Hypothes.is sidebar to leave a question or comment. Add #question to flag it for verbal discussion; #zoom for immediate Zoom chat attention. Reply to or +1 existing annotations; use @ to flag a specific person (who already commented on the page). Key uncertainties and research gaps [note]69These questions connect to S3: how should today's ground-truth from S2 shift our priors on CM's cost trajectory and AW funding value? [Suggested discussants]Suggested discussants:Matt McNulty (Tufts CCA) — strategy & operations at academic CM center; systematic view of where evidence is thinnestElliot Swartz (GFI) — wants to discuss modeling_hack + tea_review; GFI systematically identifies high-value research gaps

      European space agency tender for CM in 2021!!

    3. S1 claims: push-back from practice [?]54Which S1 technical claims do you push back on from production experience; how cost-relevant is the gap?

      An industry practitioner says: Focus on what is practical, where can I produce it, what will it cost

    4. Cell line choic

      Oana suggested that embryonic stem cells would have a consumer acceptance problem. I don't quite see why that would be (animal welfare wise, isn't it just a few cells here as the starter, not many calves)? #question ... would it otherwise be high-value

    1. Growth factors: the most uncertain cost driver

      "most uncertain" is stated a little bit too strongly here. .. Perhaps "Arguably the most uncertain "

    2. Cultivated meat — also called cell-based or cultured meat — is produced by growing animal cells in a controlled environment rather than raising and slaughtering animals. The basic idea is simple: take a small sample of cells from an animal, give them the right conditions to grow, and you end up with genuine animal muscle tissue, produced without the animal. That’s the concept. The reality involves some sophisticated biology and engineering, and understanding it is essential for anyone thinking seriously about whether this technology can become commercially viable. This overview walks through the main steps of the production process and flags where costs enter the picture at each stage.

      This is likely very oversimplified and presents concepts that are already well known to most workshop participants, but some may be less familiar with the full process.

    1. What these numbers represent: Simulated manufacturing cost per kg of cultured chicken cell biomass (wet weight, at harvest ⓘ) in 2036, based on 30,000 Monte Carlo simulations. Wet-weight hydration assumed ~80% (range ~75

      some of the tooltips are not coming up -- like here!!

    2. --- ## Interactive Model ```{ojs} //| echo: false // ============================================================ // SEEDED RANDOM NUMBER GENERATOR // ============================================================ // Simple mulberry32 PRNG (fast, good quality for Monte Carlo) function mulberry32(seed) { return function() { let t = seed += 0x6D2B79F5; t = Math.imul(t ^ t >>> 15, t | 1); t ^= t + Math.imul(t ^ t >>> 7, t | 61); return ((t ^ t >>> 14) >>> 0) / 4294967296; }

      Note, it's doing the sampling in straight javascript

    3. Growth factors (GFs) signal cells to proliferate — at current research-grade prices, they can dominate media costs. The slider below sets P(at least one scalable production route — e.g., autocrine cell lines, plant-based farming, or precision fermentation — reaches commercial scale by the projection year), switching between “expensive” and “cheap” GF price regimes. Code viewof p_recfactors = Inputs.range([0.1, 0.9], { value: urlNum("p_recfactors", 0.5), step: 0.05, label: html`P(Scalable <abbr style="cursor:help;text-decoration:underline dotted;" title="Growth Factor — signaling proteins like FGF-2, IGF-1, TGF-β that tell cells to proliferate. Currently the most expensive media component.">Growth Factor (GF)</abbr> technology)` })

      link to the learn/explainer page on the different types of potential GF innovation !

  3. Apr 2026
    1. ::: {.callout-note collapse=“true”} ## Model change log — basal micronutrients folded into media (April 2026) Earlier versions of this model carried a separate food-grade micronutrient cost line (vitamins, minerals, trace elements) with its own adoption toggle, usage range (0.1–10 g/kg), and price range ($0.02–20/g). External review flagged two problems:

      This callout block is not rendering.

    1. See Vose (2008), Risk Analysis for a textbook treatment of correlated sampling in cost models, and Morgan & Henrion (1990), Uncertainty for foundational discussion of dependent uncertainties.

      Make this a tool tip

    2. Hydrolysates

      Add as tooltip (condense a bit "What we think hydrolysates can do:

      Replace the amino acid and peptide nutritional content that serum also provides (serum is ~60% albumin, plus amino acids, growth factors, hormones, lipids)

      Possibly contain trace bioactive peptides that have modest stimulatory effects

      Reduce the amount of growth factors needed by improving overall cell health and nutrition, so cells respond better to lower growth factor doses)

      implement

    3. Code viewof reset_adoption = Inputs.button("Reset adoption defaults", { reduce: () => { // Set viewof values back to defaults viewof p_hydro.value = 0.75; viewof p_hydro.dispatchEvent(new Event("input", {bubbles: true})); viewof p_foodgrade.value = 0.65; viewof p_foodgrade.dispatchEvent(new Event("input", {bubbles: true})); viewof p_recfactors.value = 0.5; viewof p_recfactors.dispatchEvent(new Event("input", {bubbles: true})); viewof gf_progress.value = 50; viewof gf_progress.dispatchEvent(new Event("input", {bubbles: true})); } }) Reset adoption defaultsreset_adoption = 0 Code viewof p_hydro = Inputs.range([0.3, 0.95], { value: 0.75, step: 0.05, label: "P(Hydrolysates for basal media)" })

      'reset adoption defaults' button is invisible -- too dark so too little contrast with the text.

      Make reset defaults buttons more prominent throughout. #implement

    1. Table A.3 repeats the same structure using each model’s own maximum matched sample.

      doublecheck that these are NOT within the model context window

    1. Table 3.4: Human-human vs Human-LLM agreement by criterion (Krippendorff’s α)

      has this been adjusted for the fact that we're comparing the machine LLM ratings to the average of human ratings rather than to individual human ratings? If not, it's would be an unfair comparison relative to human-human (averages have less dispersion), and there's a specific way to adjust for that.

    1. Pre-booking evaluator time before paper selection (Pacchiardi); paying more for flexibility.

      This seems like a great idea to me. Talked about it in the past, as well as giving evaluators some limited choice over which ones they would like to evaluate.

    2. Strong consensus against technical AI safety expansion.

      I take this to heart, and I'm particularly concerned that we just might not have the right team to do this well. That said, I'm not convinced yet that the space is fully covered in terms of rapid, expert, credible evaluations of this research. The alignment journal, for example, is thinking of acting a bit more like a traditional journal, and it also is limited in domain, as far as I understand, to alignment research and not other aspects of technical AI safety research.

    3. reviewable documents (model cards, technical reports)."

      But peer review of model cards and technical reports would indeed bring us into a more "technical AI safety" sphere, wouldn't it? And people were generally against that, as you see in the next section.

    4. Habermacher pushes for "politically grounded ('realpolitik' type)" regulatory frameworks.

      This synthesis seems to be overly abbreviated. It's not clear what is meant by this. What sort of research are we talking about? What methods does it use? Who produces it? What ways could it be evaluated? How could it inform impactful decisions and Pivotal questions for particular funders and policymakers?

    5. gaps in "regulatory interventions,

      I need to see some examples of this work to see if it's something that fits easily with our general approach and skill set

    6. middle-power strategies and China cooperation lessons from arms control

      I need to understand this work better. What is meant by this? What are some examples of such work? I am not sure if we want to extend ourselves to less quantitative/less empirical analysis (International Relations?) I'm also not against it, but it would be a bit of a move from our current approach and perhaps our comfort zone.

    7. ugh Tagat warns "there is already a lot of ongoing work related to labor market impacts," suggesting the Unjournal should differentiate (e.g., evaluating funder-commissioned work, NBER-track pipelines).

      I don't understand this. Why is it a "warning"? That would seem to be a good thing. We're not the ones doing the research; we're the ones prioritizing it, curating it, commissioning its evaluation, bringing feedback together, pushing it towards impact, etc.

    8. AI × economics/labor markets

      Very much in our wheelhouse, and there is strong work. But does this really get at the GCR-relevant issues / the issues with the highest global impact?

    1. This requires interoperability standards across institutions, which is harder but achievable.

      This will be much easier with the use of coding tools. Standardisation will be less important/detailed

    2. Mandate open access for AI training. Require that all UKRI-funded research outputs be deposited in formats that can be used for AI training, and that this right cannot be contracted away to publishers. This does not require buying anything and it closes the loophole that allows compliance with open access mandates without genuine openness.

      Concerns about AI alignment etc?

    1. For quick inline notes on specific text or a parameter, use Hypothesis (click the < tab on the right edge). For anything beyond a brief highlight, prefer GitHub Discussions so the conversation stays organized and discoverable.

      Hypothesis comments got lost, maybe in a page change because it changed the URL?

    1. David van der Linden - Model validation Jacob Kozlowski - Financial modeling

      David van der Linden - Model validation Jacob Kozlowski - Financial modeling too strong ... they are involved

    1. grade CAPEX 5–25/kgcapacity|Basecapitalcostat20kTA|CAPEX_{}$ in scaling equation

      Clean Up the LaTeX here; it's not rendering right. #implement

    2. Media Cost=(1000density)⏟L per kg wet cells×turnover⏟media changes×price⏟$/L Variable definitions: Cell density (g/L): Final concentration of cells at harvest. Higher density = less media needed per kg. The 1000 converts g/L to L/kg (since 1 kg = 1000 g). Media turnover: How many times the media volume is replaced during a production run. Batch systems (turnover = 1) use one fill; perfusion systems (turnover = 3–10) continuously flow fresh media through. Price ($/L): Cost per liter of basal media (amino acids, glucose, vitamins, minerals — excludes growth factors, which are modeled as a separate cost component). Some literature sources report “complete medium” costs that include growth factors; our model separates these to allow independent uncertainty analysis.

      the TEA comparisons give different costs per liter, but I suppose they also give different cell densities. Should we interpret these as independent, fairly uncorrelated variables, or is the cell density more or less scaling with the price per liter in a way that using the actual cost per liter makes less sense?

      crucial_uncertainty

    1. Media cost ($/L)

      the TEA comparisons give different costs per liter, but I suppose they also give different cell densities. Should we interpret these as independent, fairly uncorrelated variables, or is the cell density more or less scaling with the price per liter in a way that using the actual cost per liter makes less sense?

      crucial_uncertainty

    1. Does gene editing regulation affect growth factor costs?

      Claude: Suggest moving this entire discussion to the workshop site. This is a workshop-specific topic about how to frame CM_01, not dashboard educational content.

      Replace with a one-line link: 'Regulatory implications for growth factor costs and how they affect CM_01 framing are discussed at our workshop site.'

      Same applies to the 'Which market?' section further down. Together these save ~40 visible lines and reduce cross-site duplication.

    2. Claude: Content trimming plan for this page (1,147 lines → ~700 target)

      Proposed changes in priority order: 1. Fold FBS/serum-free section — historical context, no longer reflects current practice. One visible sentence + collapsed detail. 2. Move jurisdiction & 'Which market?' discussions to workshop — these are workshop topics, not dashboard content. Replace with one-line links. 3. Fold GF signaling diagram — educational but not cost-relevant. Keep the price/solutions tables visible. 4. Bold audit — reduce bold to headings + key numbers only (addresses multiple reviewer comments). 5. Trim Further Resources — link to workshop resources page for full list. 6. CSS fixes — larger diagrams, less whitespace around SVGs.

      Optional: fold 2-3 SVG diagrams (cell banking, seed train) to reduce scroll length — the text already explains these steps.

      Full plan at .private/content_trimming_plan.md. Feedback welcome here or in chat.

  4. Mar 2026
    1. wo-track assessment Criteria weights depend on whether the work is prominent or not:

      Also: Let users choose their own weights with sliders as well

    2. Field-appropriate standards (don’t penalize fields where RCTs aren’t possible): Development/health: RCTs, DiD, regression discontinuity, IV Environmental/climate: Integrated assessment models, panel data, natural experiments AI governance: Mixed methods, surveys, formal models Animal welfare: Stated preference, DCEs, welfare calculations Political science: Quasi-experimental, panel data, surveys Macro/trade: DSGE, gravity equations, synthetic control

      how literally is it using these 'standards' ? This bears some more expansion

    3. In an economy with manual labor, cognitive labor, physical capital, and AI, optimal tax policy can include taxing AI.

      provide tooltip quotes to check for hallucination

    Annotators

    1. The diagram compares these two operating modes side-by-side. Batch mode (left) harvests everything at once; perfusion (right) continuously adds fresh media and removes spent media while retaining cells.

      too much white space before and after image

    2. The opportunity: If cultured meat can use simplified food-grade designs (similar to beer brewing at $5-15/L), costs could drop by 10×.

      are they already doing this? If so, maybe adjust the wordking/emphasis here

    3. of cells matters enormously for cost:

      "enormously for cost' Seems potentially too strong here. ... as we have suggested above, the estimated cost share for cell banking is less than 1% of the total cost.

      Am I correct? If so, please moderate this.

    4. Step 1: Cell Banking

      For each step, give a 'tldr' and an estimated cost share, and have the rest be something folded by default, which they can unfold

    5. Today, optimistic projections suggest ~$63/kg (Garrison et al. 2022), with leading companies achieving <$10/kg cell mass.

      Flag a note (more discussion in tooltip) about how this is the cost of pure cell mass, and early/ultimate products might be hybrid CM, plant-based, fungal etc. ... so this overstates the cost, in a sense

      "Achieving $10/kg" is probably too strong. Maybe 'claiming the ability'? And do you have a link to this?

    6. Product

      diagram below a bit small. Last item looks like a drumstick -- maybe make it look like a 'chicken hamburger' instead? (Because early products unlikely to have bones)

    7. key levers

      The high cell density is in blue, but you also put "micros" in blue, which suggests the two have a link. I don't think that's what it is. I think the high cell density will reduce the media cost, which is in green, and maybe other goals like bioreactor and operating expenses so I'm a bit confused.

    8. Typical Cost Breakdown ($/kg chicken)

      Diagram below does not really make sense. Is it a breakdown of the cost components or something having to do with levers that could make the costs go up or down substantially? This needs more clarity.

    9. How Cultured Chicken is Made Code

      Top of this, or maybe on another page, it would be nice to have some sort of mosaic graph with different cost break-downs for different scenarios. Dividing up the cost into different components to get to total cost per kilogram, and then perhaps each of those mosaic elements could link to a different section explaining it.

    10. This reasoning underlies our model’s binary switch approach —

      This part of the model and also define what you mean by "binary switch" specifically in a tooltip.

    11. insulin and transferrin

      I don't think these were mentioned anywhere either - Dash. Are these growth factors? If they're not growth factors, why are you discussing them in this section?

    12. Current Price Target Price

      It doesn't really matter what the price is per gram of inpuy . The question is, what is the likely price per kilogram of chicken meat output. add a column for this.

    13. Key Growth Factors for Cultured Meat

      Why are you telling me about all these different kinds of growth factors? Do they all need to be used? Are they alternatives to each other? Have you defined what the terms in the "function" column mean?

      And how much of them will need to be used per kilogram of chicken meat produced (or whatever weight we are standardizing things to here), what cost implications? Right to always bring things to this standard unit of cost per kilogram of chicken meat.

    14. Cost ($/L)

      How does dollars per liter map into dollars per whatever unit of chicken meat we're using here? It's going to depend on the cellular density. I presume the cellular density is the same for these two types of media, or does one lead to much less dense cells?

    15. Hydrolysates: The Big Win for Amino Acids

      To what extent is it clear that these can just simply be used, and to what extent is this still an important uncertainty? If it's clear that they can be used, We should make that clear-- to flag this so people don't think of it as still an important uncertainty. But we should look for more references here to be sure.

    16. The cultured meat industry must use serum-free media.

      Try not to state things in a very prescriptive way. We're meant to be providing background information, not ordering people around.

    17. This is THE Pivotal Uncertainty (click to expand)

      Again, this really just seems too strong a statement to make. We need a little bit more epistemic modesty and reasoning transparency.

    18. expand

      Maybe rewrite the headline to actually say that the total media cost is predicted to be out 40 to 70% of production cost, or whatever the numbers tell us. I don't need to expand it to get the headline result.

    19. Ethical: Derived from fetal calves — defeats purpose of avoiding animal slaughter Limited supply: ~500,000 L/year globally (van der Valk et al. 2018)

      Where does the supply come from? Are animals being killed here to produce it?

      This might be a folding box. I'm not sure if it enters into the previous narrative. ?

    20. Traditional cell culture uses fetal bovine serum (FBS) — a complex mixture that provides growth factors, hormones, and attachment proteins. Problems:

      So which of the above is this used for? It seems like it covers several of the above things you're calling "media". That's a little bit confusing to have this overlap of some sort.

    1. Optimistic TEA ($6/lb) — useful comparison but model does not replicate their specific assumptions

      I don't think this is for pure cell mass, this is for a hybrid product

    2. These are like Squiggle/Guesstimate visualizations - they show the full range of possible values, not just a point estimate.

      Based on which parameters? the user-entered ones above?

    3. Basic Parameters Code viewof plant_capacity = Inputs.range([5, 100], { value: 20, step: 5, label: "Plant Capacity (kTA/yr)" })

      Important -- are these means or medians of a distribution used in simulation or are these simple 'degenerate' numbers. Explain and signpost better

      And do they affect the figures and graphs below? #important

    4. Individual distributions for each cost driver: Code function formatCost(val) { if (val >= 30) return Math.round(val).toString(); if (val >= 1) return val.toFixed(1); if (val >= 0.1) return val.toFixed(2); return val.toFixed(3); } { const allComponents = [ {name: "Media", data: results.cost_media, color: "#27ae60"}, {name: "Micronutrients", data: results.cost_comm_micros, color: "#3498db"}, {name: "Growth Factors", data: results.cost_recf, color: "#9b59b6"}, {name: "Other VOC", data: results.cost_other_var, color: "#7f8c8d"}, {name: "CAPEX (annualized)", data: results.cost_capex, color: "#e74c3c"}, {name: "Fixed OPEX", data: results.cost_fixed, color: "#f39c12"}, {name: "Downstream", data: results.cost_downstream, color: "#1abc9c"} ]; // Filter out components with all zeros (e.g., downstream when not included) const components = allComponents.filter(c => mean(c.data) > 0.001); const plotData = components.map(comp => { const p5 = quantile(comp.data, 0.05); const p50 = quantile(comp.data, 0.50); const p95 = quantile(comp.data, 0.95); const clipVal = Math.max(quantile(comp.data, 0.98), 0.1); const clipped = comp.data.filter(x => x <= clipVal && x >= 0); const plot = Plot.plot({ width: 420, height: 180, marginLeft: 45, marginBottom: 35, marginTop: 10, x: { label: "$/kg", domain: [0, clipVal * 1.1] }, y: { label: null, ticks: [] }, marks: [ Plot.rectY(clipped, Plot.binX({y: "count"}, {x: d => d, fill: comp.color, fillOpacity: 0.7})), Plot.ruleX([p5], {stroke: "black", strokeWidth: 1.5, strokeDasharray: "3,3"}), Plot.ruleX([p50], {stroke: "black", strokeWidth: 2}), Plot.ruleX([p95], {stroke: "black", strokeWidth: 1.5, strokeDasharray: "3,3"}) ] }); const label = `${comp.name}: $${formatCost(p50)} (90% CI: ${formatCost(p5)} – ${formatCost(p95)})`; return {plot, label}; }); return html`<div style="display: grid; grid-template-columns: repeat(2, 1fr); gap: 1rem; margin: 1rem 0;"> ${plotData.map(d => html`<div style="font-size: 0.9em;"> <div style="font-weight: normal; margin-bottom: 0.3rem; color: #333;">${d.label}</div> ${d.plot} </div>`)} </div>`; } formatCost = ƒ(val)

      Do these adjust as I change the sliders above? I changed the 'plant capacity' and I did not see any change here. What's going on? #important

    5. Cost Breakdown by Component (Total: $122.51/kg):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 the graph below a bit bigger

    6. Price-competitive with conventional chicken

      Wait -- adjust this to consider/note the CM inclusion rate (%) and cost of plant-based or mycoprotein ingredients ($/kg)

    7. edian Cost (p50)

      Have a separate number for each of these boxes (slightly less prominent) for 'hybrid product cost/kg' ...

      User should be able to input a 'CM inclusion rate (%) and cost of plant-based or mycoprotein ingredients ($/kg) as parameters', and this should do a simple auto adjustment.

      First just a simple adjustment, and later we make this part of the simulation model.

      Also allow user to switch this 'hybrid product' on/off (box below 'Include downstream processing'

    8. Why it matters: If production costs reach ~$10/kg (comparable to conventional chicken), cultured meat could compete at scale. If costs remain >$50/kg, the technology may remain niche

      Caveat/note here about cost of producing the pure cultivated chicken cells, vs cost of the product that will have some percentage of these cells mixed with other (plant, fungal, etc.) ingredients.

    9. Probabilities, fractions

      Note that for ~switching parameters, the model samples both from the probabilities of a switch to a different regime (a different discrete state of the world, e.g., a new discovery) and then, in each simulation, uses this probability to select a particular state. (word this better, and be sure I'm correct here)

    1. This model helps evaluators and forecasters:

      But atm we donm't have confidence in this model. I's more about fixing ideas and giving people a sense of what sort of modeling we want (and surfacing doubts and disagreements on this) so that we can productively collaborate.

      Ideally, we'd also have a page/interface where people could 'build their own models' and we compare them.

    1. New to this topic? How Cultured Chicken is Made | 🎧 Audio Review (22 min MP3)

      Skip this last bit. Try to condense the content at the top a bit more for this page

    2. 🔬 Workshop: Cultured Meat Cost Trajectories (Late April / Early May 2026) This model feeds into The Unjournal’s upcoming expert workshop on CM production costs. Workshop details & signup →

      Don't need this at the top of the technical reference page.

    1. If the price of high-quality plant-based hamburgers fell by 10% everywhere, how would global chicken consumption change?

      Explain why we targeted this 'cross category' substitution. We understand it's initially counter-intuitive. TLDR: Impossible Beef is a defined category with fairly clear pricing and high quality, but chicken consumption is more animal-welfare-relevant than beef. But we have variants of this that are more within-category. Put the TLDR in a tooltip and a longer explanation in a folding box.

      Some more detailed explanation at https://forum.effectivealtruism.org/s/kazWBBYXm2Rvya3y2/p/3Eh8MbqLwFBsD7GK2#Why_focus_on_chicken_consumption_ and https://forum.effectivealtruism.org/s/kazWBBYXm2Rvya3y2/p/3Eh8MbqLwFBsD7GK2#Why_focus_on_Impossible_Beyond_Beef_

    1. Decision RelevanceUnderstanding the nuances of poverty traps and 'trappedness' can inform development policies and interventions aimed at poverty alleviation. This paper could provide insights into where resources and policy changes would be most effective globally.

      This feels a bit vague to me. Are there specific policies that would be affected?