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?
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
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
grade CAPEX 5–25/kgcapacity|Basecapitalcostat20kTA|CAPEX_{}$ in scaling equation
Clean Up the LaTeX here; it's not rendering right. #implement
echnical Reference
Rename as "Model formulas" #implement
Session prep, agenda, follow-ups, and broader workshop-level discussion tied to the April 2026 Cultivated Meat PQ Workshop.
should be May
Media cost ($/L)
the TEA comparisons give different costs per liter, but I suppose they also give different cell densities. Should we interpret these as independent, fairly uncorrelated variables, or is the cell density more or less scaling with the price per liter in a way that using the actual cost per liter makes less sense?
Goodwin et al. 2024 (Nature
Add a link to this paper and to other papers within the table (a hyperlink) to save people time.
Media Cost=(1000density)⏟L per kg wet cells×turnover⏟media changes×price⏟$/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?
Claude: Resources page shortening suggestions:
Remove duplicate tool cards — the Dashboard + Learn page cards are identical to what's on the About page. Replace with a compact one-liner: 'Interactive tools: Dashboard · How CM is Made · TEA Comparison · Technical Docs'
Add TEA Comparison link — the new compare.html page systematically compares Pasitka, Humbird, CE Delft, GFI, and Goodwin. This is directly relevant to the reading list context.
Keep the Shared Reading Collection — it serves a unique purpose (downloadable PDFs) not available elsewhere.
Keep the PQ Database section — it's the canonical link set.
Claude: Workshop page shortening suggestions:
Remove the 'Suggested Reading' fold (lines 103-124) — this duplicates the reading list on resources.html. Replace with: 'See our Resources page for suggested reading and key papers.'
Tighten crux card descriptions — now that the dashboard has a dedicated TEA Comparison page, the crux cards can be 1-2 sentences shorter. Link to compare.html for detail.
Add compare.qmd to the tool cards alongside Dashboard and Learn page.
Estimated savings: ~40 lines, plus reduced reader burden from not seeing the same reading list twice.
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.
The Serum-Free Challenge
Claude: Suggest collapsing this entire FBS subsection into a single fold titled 'Historical note: Why the industry moved to serum-free media.'
One visible sentence: 'All commercial cultured meat uses serum-free media — here's why the industry moved away from fetal bovine serum.'
The detailed explanation (what FBS is, why it can't scale, ethical issues) is educational but no longer reflects current practice. Nobody uses FBS. Folding saves ~25 visible lines and keeps the page focused on current cost drivers.
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.
1. Global Decision-Relevance (most important)
this should be specified somewhat by field
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
5. Methodological Potential
is it a 'strong data set' etc
Animal w
How do we prefer stated preference here? I think revealed preference and real choices are more credible
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
NBER working paper,
caveat this if it's a conference paper
Show detailed scoring rubrics & methodology
Make this more prominent.
Key Claims to Evaluate
add a category -- 'methodological and theoretical/technical issues to be evaluated ... rate 'evaluability'
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
What’s the chance that production costs fall below key price points
Not bold, avoid bold.
To explore these costs interactively, see our
not bold. Too much bold in general
optimistic
how is that 'optimistic?'
Note -- I want direct quotes from original sources (in tooltips) for important quant claims
Cells grow on scaffolds, media flows through
K: scaffolding may not be a cost-effective option, low cell densities
2024: PMC meta-analysis (Garrison et al.),
Where is this used? I mostly see the earlier sources mentioned above.
Source
The diagram is still too small. Make it bigger, please
all
not bold
Research Price Production Target Source
can you have columns with the cost/kg of output for each of these, at each of the prices
Cell densities have improved dramatically:
keep this prominent (out of fold)
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
Batch vs. Perfusion: Two Operating Modes
give a tldr and the rest should be a folding box
underscores why most cultured meat companies currently use pharma-grade equipment despite the cost premium.
Is that still true?! Source please
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
Relative cost
give absolute cost/Kg too
2021
whose?
$10-15/kg, with some leading-edge companies achieving costs below $10/kg”
who is this quote form? "achieving" needs a reference
grade
at what cost/L?
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.
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
: <1% of total production cost at scale
references Humbird and Risner -- adapt htis to also reference work from GFI
Seed Train
missing bold label in diagram for this
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 $10/kg" is probably too strong. Maybe 'claiming the ability'? And do you have a link to this?
Product
diagram below a bit small. Last item looks like a drumstick -- maybe make it look like a 'chicken hamburger' instead? (Because early products unlikely to have bones)
🔬 Workshop: Cultured Meat Cost Trajectories (Late April / Early May 2026)
make these folding boxes with extra content in tooltips
key levers
The high cell density is in blue, but you also put "micros" in blue, which suggests the two have a link. I don't think that's what it is. I think the high cell density will reduce the media cost, which is in green, and maybe other goals like bioreactor and operating expenses so I'm a bit confused.
Typical Cost Breakdown ($/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.
growth factors
Hyperlink is not working so well
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.
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.
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?
albumin
What is albumin? You did not mention it anywhere else in this document. Is it a growth factor?
Solutions Being Developed
Which of the growth factors do these "solutions" pertain to?
Market data
Where did you find the market data ?
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.
Most companies scaling up have already adopted hydrolysate-based media.
Tooltip example here, please.
most companies
Give listings, examples, and links/citations with tooltip quotes.
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.
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?
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.
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.
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.
serum-free media d
Another hovering "?" here
Global FBS supply: ~500,000 L/year
Where exactly does it come from though?
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.
0-70% of total production cost (Humbird 2021, Risner et al. 2021).
Any way you could cite more recent references?
<5% if breakthrough technologies
Which ones give an explanation, maybe in a tooltip?
research scale
But why focus at research scale? Could you give what is projected to be a production scale?
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. ?
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.
grade (Sigma-Aldrich pricing)
Give me some excerpts from that page and explain what it means. You just linked to a sort of commercial page. It's not very helpful or easy to navigate.
Traditional cell culture uses fetal bovine serum (FBS)
A question mark comes up when I hover over this, but I don't see any tooltip explaining what it is.
Also, why are you talking about bovine serum if we're thinking about chicken here? At least you should explain the analogy.
Moderate
Quantify this.
Vitamins Metabolic cofactors B-complex, etc. Minerals/salts Osmotic balance, enzyme function
Maybe group the cheapest things together in one row unless there's some sort of environmental or ethical issue with them.
FGF
Tool tips should explain what each of these things are.
costs
Not all costs, just this component of cost. Again, I want to know what share that makes up of the total to put this in perspective. It's only a minor share of total cost. It's not really a pivotal cost driver, is it?
Try to put these in terms of cost per unit of meat produced in a mature production process, and try to use the same units everywhere so we know how to compare each element and sub-element.
Cell culture media contains everything cells need to grow:
List these by order of estimated share of cost in a production-scale process. And give a rough estimate of those shares, and those should be on the same scale - expressed per unit of output, in the same units. Give a disclaimer, of course, that this is just based on one particular estimate, and you can link to the actual model.
Hydrolysates vs. pure amino acids
What share of media costs are these in different models and reports? I thought this was possibly the largest?
media turnover parameter in our model
Link this part of the model. Backlinks might also be good from the model to this explanation (here and everywhere else. )
sio
Batch versus perfusion? You haven't given enough narrative here. I don't know why you're telling me this. Are these different bioreactor types, and if so, how does it map into the categories you just gave above?
Simplified designs for food production
This is a little confusing to me because what do you mean designed for food production? What is the standard food production use of this if not for cultured meat?
Batch vs. Perfusion
These images below are also too small.
Source
These sources are all from 2021 or earlier - can't you find some updated cost figures?
Bioreactor Types
Link some pictures of these types of tanks, or perhaps a folding box showing these pictures. You'll have to do a web search to look these things up.
ou need far fewer reactor transfers
What's the typical cost of the reactor transfer in an established, larger-scale production process? Would this still be a substantial share of total costs?
less total media.
But isn't the sort of media that achieves higher density more expensive? I'm actually uncertain about this.
often pharma-grade at $5-20/L
Source for the quote "often pharma grade?" Okay, you're relying heavily on Humbird here. Find some other sources, and I've heard that now most companies are using food grade instead of pharma grade. Look into that and discuss in tooltip footnotes.
Cost Impact
For each phase, I want you to give some indication of the share of costs, in terms of the total cost per unit of meat, that this could potentially encompass, both at a small scale and at a larger scale.
Seed Train: Progressive Scale-Up Vial 1 mL 10⁶ cells T-Flask 100 mL 10⁷ cells Spinner 1 L 10⁸ cells Small Reactor 10 L 10⁹ cells Medium Reactor 100 L 10¹⁰ cells Production 1,000+ L 10¹¹+ cells
The text is a bit crowded here, so the numbers overlap the words. Try to adjust to give it a little more space.
Step 1: Cell Banking What Happens
Give more continuous references, perhaps as tooltips, to where you are getting this information from about the process. Perhaps give citations with links and short quotes.
require regulatory approval.
Link to this regulatory approval thing - how difficult/Costly is it to get that approval, or do we already have this for the important immortalized cell lines?
one-time setup cost that’s amortized over many production runs. A well-characterized cell bank can support years of production (GFI 2021).
Doesn't really explain how the costs work. Ultimately, the banked cells are used up, correct? Are you saying that cell banking is just a tiny share of the cost here, if you end up using the whole batch, is that right?
1. Biopsy
Image is still a bit too small.
2. Isolate Cells
Are we trying to isolate and why? Maybe this is a tool tip? And what's enzymatic digestion?
Step 1: Cell Banking
You did not use the term "cell banking" in the flow chart above. This can be confusing when you change terms. We don't know what Maps to what
Pasitka et al. 2022
Give the name of the paper and a tooltip, and also explain what aspects of these claims the source provides, perhaps with quick quotes.
Similar FGF-2/IGF-1 requirements to bovine (~10-100 ng/mL optimal)
Explain, perhaps in a tooltip, why the similarity is helpful here. That I don't really know what these things mean (e.g., what does ng mean?)
~70 billion chickens slaughtered annually vs ~300 million cattle
Provide a tooltip/link to discussion from animal welfare advocates about this, perhaps on the EA forum.
Kim et al. 2024
Tooltip hover should show the name of the paper, et cetera.
Produc
Can you make an image without a bone in it that still looks like a piece of chicken meat? I don't think bones are happening any time soon in cultured meat.
Seed Train
What's a seed train?
Step 5: Growth Factors — The Pivotal Challenge
Seems too strong. Media costs exceed GF costs in many formulations I've seen.
This is THE pivotal uncertainty. If any of these approaches succeeds at scale, growth factors become negligible (<$1/kg chicken). If none succeed, growth factors could be >$100/kg — making cultured meat uneconomic at scale. See GFI’s analysis for detailed technical roadmaps.
this seems a bit too strong from my reading. Media costs exceed GF costs in many formulations
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
Limitations
folding box
Results update automatically as you change parameters - no need to click a button.
I'm not sure all results do, maybe only the top boxes?
0 = nascent, 1 = mature
a continuous variable I guess, not binary. Make this clearer to avoid confusion
Cultured Chicken Production Cost Model CodeShow All CodeHide All CodeView Source
More caveats about this model ... largely AI generated, as of 27 Mar 2026 we can't vouch for the numbers, provided to give a sense of the sort of modeling we're interested in, and present a framework for discussion and comparison
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?
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
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
Sources
only these 3? Does the model incorporate other info?
The model reveals several important patterns:
which model? Does this adapt dynamically?
WACC Low (%)
give some tooltip explainers here
Cost Breakdown by Component (Total: $122.51/kg):where(.plot-d6a7b5) { --plot-background: white; display: block; height: auto; height: intrinsic; max-width: 100%; } :where(.plot-d6a7b5 text), :where(.plot-d6a7b5 tspan) { white-space: pre; }
make the graph below a bit bigger
Price-competitive with conventional chicken
Wait -- adjust this to consider/note the CM inclusion rate (%) and cost of plant-based or mycoprotein ingredients ($/kg)
Plant Capacity (kTA/yr)
Where did the slider range and starting value come from? Explain in a tooltip
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'
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.
What these numbers represent: Simulated production cost per kilogram of cultured chicken (wet weight, unprocessed) in 2036, based on 30,000 Monte Carlo simulations. This is the cost to produce meat in a bioreactor — not retail price, which would include processing, distribution, and margins.
Make it clear that we're giving the cost/kg for pure chicken cells, not the consumer product, which may (likely?) involve a small to moderate fraction of these cells in the output. Thus the 'price parity with conventional meat' might be easier to attain than the raw numbers suggest.
Make a prominent note (and unfold further discussion) about the production cost of pure cultured chicken cells versus the cost of the products offered, which are likely to include a mix of chicken cells, plant elements, maybe fungal elements, and other things.
Thus the cost per kg of pure chicken might not be assessed
Include capital costs (CAPEX)
why wouldn't you include these?
A key feature is the latent maturity factor that links:
provide a reference for this approach, and provide and link a more detailed explanation
Lognormal
Note that we're open to considering other distributional forms, and making the modeling flexible to allow for different (chosen or simulated) distributions
Bounded ranges
give some specific examples of cases where this is used
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)
NoteWe Want Your Feedback!
no "!"
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. Total Unit Cost
This should probably be mirrored or linked a bit more on the man quote model page so people understand where it comes from.
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
🔬 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.
Related Workshops
you don't need to put this here because it's not a 'resource' for this question
Dullaghan & Zhang (2022)
link the original paper/post as well as our evaluatinos
Forecasting & prior Unjournal work
It's not really 'unjournal work'
Found
Still a bit too strong to say 'found' -- this is their result -- the document should not endorse it nor criticize it
⭐ GFI amino acid report (Dec 2025) — GFI. Based on real quotes from amino acid suppliers and CM manufacturers. Found Humbird's amino acid prices overestimated by 2–10x. GFI cell growth modeling (Nov 2025) — GFI. How to model cell growth more realistically than current TEAs. GFI growth factor costs (2023) — PDF. Anticipated growth factor and recombinant protein costs and volumes for cost-competitive CM. GFI medium cost analysis (2020) — GFI. Foundational analysis of media as the dominant variable cost; identifies recombinant proteins and growth factors as key cost drivers. Some companies report 60% media cost reductions using plant-derived protein homologs. GFI scale-up & bioprocessing trends (2024) — GFI. Industry trends in bioreactor scale, continuous perfusion, and food-grade equipment — relevant to CM_16 (cell density) and CM_20
too many here (and also all from a single source, GFI. Try to diversify sources, but also use folding and tooltips to reduce the clutter
Media costs & supply chain
these are all GFI!! are there any other sources we could find?
GFI amino acid report (Dec 2025)
Link actual report
Note: Believer Meats (the authors' company) shut down Dec 2025.
this feels a bit too ad-hominem an attack. A tooltip can mention the author's relationship to the company but should not imply that it nullifies the arguments made. See if the author themself made any points about this
Lynch & Pierrehumbert (2019) — "Climate impacts of cultured meat and beef cattle." Early TEA with environmental dimension.
skip this one maybe? I don't want to focus on Climate
(we monitor and respond to all comments)
'aim to respond'
corporate campaigns
'corporate AW campaigns'
per dollar of THL campaigns.
"THL" is not clear here. What is that? Instead 'best other intervention category'
in 2036
add tooltip -- "You can provide projections for future years in the discussion section, if desired"
▸ Context & reference points Optimistic TEAs: Pasitka et al. (2024) claims ~$6.2/lb ($13.7/kg) is achievable with continuous production and animal-free medium. Pessimistic TEAs: Humbird (2020) concluded cost parity is "highly unlikely" given biological and engineering constraints. Current conventional chicken: ~$2-4/kg wholesale in the US. Rethink Priorities (2022): Forecasted limited production through 2050 under most scenarios.
I don't think I want to show these - these will anchor people based on our own previous review in ways that we might not want
How many chickens will be slaughtered for meat globally in 2032 and 2052?
skip this one ... too indirect #implement
What is the expected-value (and probability distribution) of the impact on animal welfare from funding CM development? Consider marginal funding, very high funding levels, or impact relative to the best alternative interventions.
Give an (optional) slider for them to state what share of benefit, relative to the next best intervention, is achieved, along with 80% CIs
The answers also inform animal welfare funding decisions, but the workshop focus is on getting the cost evidence right.
This last sentence seems out of place.
cruxes
Prematurely definitive. Make it more like "organizing discussion around key cruxes such as"
4. From TEA to reality: Why did Believer Meats fail?
I haven't wanted to make this central. It's worth mentioning, but I wouldn't make it the 'headline' of the fourth point
GFI's recent work
tooltip reference and link with a direct quote
Pasitka
give tooltip links and direct quotes, with dates and paper names #implement -- important
See our EA Forum post for further discussion.
"July 2025 EA Forum post' -- make this a tooltip #implement
spare billions of animals. I
Tooltip here about how we note there may be a range of other important benefits and perhaps costs here, including environmental benefits, reduction of animal-to-human disease vectors, etc., but we are mainly focused on animal welfare for this conference.
We're now commissioning evaluations of key TEAs,
Not quite -- these will come out of the PQ project -- see the 'request to evaluators' here: https://coda.io/d/Unjournal-Public-Pages_ddIEzDONWdb/Cultured-meat-PQ-Request-to-TEA-evaluators_suyucPLB#_luoC2X-O
pessimistic
Add a link here: "See our EA Forum post for further discussion." (hyperlink https://forum.effectivealtruism.org/posts/7ha23d3qzXiCqYLDq/is-cultured-meat-commercially-viable-unjournal-s-first)
The core question is deceptively simple: What will cultivated meat cost to produce? If costs fall dramatically, CM could displace a substantial share of conventional meat production and spare billions of animals. If costs remain high, funding CM development may have been a poor use of limited animal welfare resources compared to proven interventions.
This is a bit too simple -- see other discussion pages. For the 'what to fund' question, we need to consider the marginal benefit of funding on the probability and magnitude of success in fostering CM (sooner) and displacing animal products and animal suffering. This is discussed too much more detail in the specific PQ definitions, motivations and resources.
But "CM is plausibly able to achieve near price parity" seems highly correlated or causally entangled with "funding CM development (and supporting it politically) is likely to have high AW impact per dollar". IN particular, if it seems practically impossible for CM to ever get close to near parity. Then it seems unlikely that the CM project will be successful and thus a near guarantee that additional funding will have little impact.
But we should note or at least footnote that that's more of a necessary than a sufficient condition. CM funding could have a low impact/$ for other reasons, e.g., if, on the other hand CM is likely to be successful soon irrespective of this funding.
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_
PBA_01 · Focal Question · Substitution Effect
I'd link the Metaculus question right next to each question here.
Which Potential Segments Interest You?
Add some other potential segments, perhaps
"business, government, and philanthropic environment and the cost of capital."
"How is cultured meat produced -- a cost-focused background overview"
"Constructing TEAs, uncertainty modeling, and forecasting" -- hands on modeling (post-workshop hack session, 2-5 hours)
comment
Still add your annotations and let me know what you think about hypothesis as a format for collaborative discussion.
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?
DRAFT — This survey will be available after the workshop takes place. Questions?
Make this less prominent -- no 'header' until after the workshop
Can reverse cross-population comparisons.
remember -- we are not focused on cross-population comparisons for this workshop. It's more about 'which interventions yield greater welfare', which would generally involve differences in difference, ideally across comparable populations (but not always)
δ = discount factor for future years
Where did the discount and time factor come from? Where did these definitional equations come from? I didn't think most emply estimated WELLBY measures considered multi-year collection or impact. And are they really discounting?
what most intervention comparisons need)
Cut this. I don't think it necessarily holds -- a lot of interventions impact mortality.
Add to footnote -- the 'incremental' WELLBYs may be captured by observing differences between comparable treated and untreated populations.
Accounting
it's not really 'accounting' -- these are conceptual
UK Government: Official guidance for policy appraisal
A link to this would be helpful. The "Green Book". (I wonder -- how impactful has this actually been on British policy?)
Neutral point estimation: What is the actual neutral point on the 0-10 scale for different populations? How stable is it across contexts?
I suspect we don't have any good measures of this? There's the Peasgood paper but I don't think that was in a LMIC and I'm not sure how much it has been vetted?
Annotate & Comment: Double-click any text to add a Hypothes.is annotation. No account needed to read; quick signup for a free account to post.
We'd especially like pre-session feedback on
Even if you accept WELLBY as the target unit, the measurement layer forces choices:
underexplained/too brief perhaps
layer
why do we use the word 'layer' -- is this the term in the literature?
close to linear
"Close to linear" is interesting -- a footnote could expand on this a bit
Predictive validity: SWB predicts consequential outcomes systematically
This was mentioned above, but does it do so in a scale-sensitive way?
As I suggested, it's not enough to have it be 'somewhat predictive'
Transformation Sensitivity Demo
This needs more context and explanation. I've forgotten what g of x is here, and what's the actual calculation? Also, this doesn't seem to be illustrating the point that it means to. As I move the slider, population B always seems to be higher, but also it seems like we're getting away from the discussion of the relative impact of different interventions. We don't want to just simply compare populations. If this does pertain to interventions, explain better.
Exokain a bit more (as a footnote) what the 'transformation' means here and why/when it's used
Magnitude-sensitive cost-effectiveness: Even if signs are stable, cost-effectiveness ratios rely on magnitudes
Do they? Magnitudes of what? Explain. Give a 1-2 sentence exampls as a footnote
Incremental WELLBY Estimate
This is simple and perhaps obvious, but good for illustrating the simple WELLBY linear WELLBY concept, but that's already been explained above. I'm not sure what should maybe be put at the top. I'm not sure if it's useful down here. OK put this at the top, in a folding box -- it just helps to make sure we're all in on the same page about the definition of the WELLBY here.
Perhaps it would also be helpful to include some sort of adjusted WELLBY calculator interface that's a more sophisticated concept people might not appreciate, particularly embodying the approach in Benjamin and others.
What "non-identified" means A parameter is "identified" when data + assumptions pin down a unique value. Ordinal responses only tell us which interval a latent value falls into. Many different latent distributions and transformations can generate the same observed category counts, so rankings of means can change across equally admissible representations.
This explanation is not clear. It could be improved, it's a bit too literal. Why do ordinal responses only tell us in which interval a latent value falls into?
This might also be worth folding
2. Definitions and key concepts
add a bit more 'narrative' here
directly via experimental comparison.
comparison of what -- be more precise
Monotonic transformations can reverse conclusions
An example here would be very helpful. ... Perhaps even an interactive display.
Monotonic transformations of what?
We may quote specific responses with attribution unless you request otherwise. If you prefer your responses remain anonymous,
Adjust this -- "If you prefer your response to remain anonymous, please use a pseudonym and try to use the same one consistently if you're providing multiple responses." If you are fine with internal recognition but don't want any public attribution, please let us know and share any other concerns in the field at the bottom.
How likely is it that the simple WELLBY measure (as defined above) is the best or near-best measure—yielding no less than 80% of the value of the best measure—for cross-intervention comparison in the focal context? (State your best calibrated probability.)
I'm considering adjusting this one to
Consider the 'value obtained when using the best feasible measure for cross intervention comparison in contexts like the focal context'. What share of this value is obtained, in expectation, from using the simple linear WELLBY measure for all interventions? Please give your central belief, and 90% credible intervals"
-- with a slider that goes from zero to one, and two other sliders that allow that allow you to specify the lower and upper bound of the 90% CIs.
emonstrates that small transformations can reverse published findings.
NotebookLM:
"they applied their methodology to nine prominent results from the happiness literature—including the Easterlin Paradox, the U-shape of happiness in age, the ranking of countries by happiness, and the effects of marriage and children—and showed that the standard conclusions in all nine areas could be reversed using monotonic (specifically lognormal) scale transformations. They argued that these reversing transformations were "plausible," claiming they were no more skewed than the U.S. wealth distribution
However, later work questions the plausibility of this. .
A systematic conceptual defense of treating wellbeing scales as cardinal and comparable. Argues that deviations from cardinality are small and not policy-relevant.
See https://www.econstor.eu/bitstream/10419/232657/1/dp13905.pdf
Start here (30-60 min total)
It will take more than 60 minutes, but a skim might be doable in 60 minutes.
Confirmed Participants (15) — click to expand
Add "(rsvps)" -- Also update this, I think we have over 20 by now.
Note: human means carry their own variance; correlations here are bounded by human inter-rater noise.
is this ggplotly? Shouldn't it be dynamic? I don't seem to be able to adjust it
Table 3.1: Token usage and estimated cost per model
These are probably not updated costs -- Update and implement
Alberto Prati may contribute via pre-recorded video.
Not 'video', possibly some written content, or we can extract issues from his evaluation to ask Benjamin et al.
leads to least regret?
The "least regret" is a formal term in information theory, I believe, or from Bayesian updating. Provide a footnote defining and referencing it. #Implement
Annotate & Comment:
We'd especially like pre-session feedback on
ng "average happiness"
But we're focused on interventions, not on average happiness between groups. - Be more specific to this. #Implement
The key critique
--> "A key critique"
biasing
'potentially biasing'
not a corner case.
what's meant by 'corner case' here?
MH
what's MK? I forgot. Has it been defined?
Most studies measure outcomes at baseline and one or two follow-ups;
Give a footnote with some examples here. What do the studies involving LMIC interventions do?
cancels
'cancels' is vague -- explain what is meant here in a footnote. #implement