Give your independent forecast of cultivated meat production costs and explain the assumptions behind it. A full response is estimated to take 45–60 minutes; partial responses are welcome.
Start with the cost question · About you and submit
We want your own view first. We're deliberately not showing you other people's estimates or any model output at this stage — we don't want to anchor your judgement. Once we've gathered this round of independent forecasts, we'll circulate the combined picture and the main points of disagreement, and invite you to revisit and update your estimate. For now, please answer from your own knowledge and reasoning. Naturally, we encourage you to consult your own notes, do a background web search, run calculations, etc.
Thank-you for your time
The four initial $100 response slots are provisionally filled as of 31 July 2026. Earlier individual commitments still standIf you were promised an incentive for responding by a particular date, we will hold to that promise. If you have any questions, email contact@unjournal.org. A further $50 is reserved for eligible respondents who return for the follow-up/update round. Please check with us before assuming that a new response is compensated.
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You can consult your own sources and calculations. Please identify any model or other forecast you used in your reasoning.
How to give estimates and uncertainty ranges
- For cost estimates: Give your median estimate and your uncertainty bounds (p10 and p90). [how to form them]Recommended order (Anca Hanea, IDEA protocol): think about your lower bound first — all the reasons costs could be small — then your upper bound — all the reasons costs could be large — and then the median. Starting with the median and adding bounds afterwards leads to intervals that are too narrow. See the guidance fold below for the full approach.
- For probability questions: State your best calibrated subjective probability. (See "How should I think about probability estimates?" below.)
- For open-ended questions: Even a sentence or two helps. We're looking for reasoning and considerations, not polished analysis.
- For numeric fields: Placeholder text shows format only — please form your own estimate before entering a value.
- You can return and update your responses as your views evolve.
Please estimate independently. Please give your own knowledge and judgement, rather than looking up what any cost model assumes. Your own knowledge, judgment, and calibrated uncertainty is what's informative. [if you do use it]If you do consult a cost model and use its sliders or central estimate as a reference, that's fine — but please note this in your reasoning field or a Hypothes.is comment, and explain what you changed and why. A comparison between your independent view and a cost model's assumption is useful information too.
▸ Guidance on forming your estimates and uncertainty bounds (Anca Hanea) (unfold)
Anca Hanea (U Melbourne), expert in structured expert elicitation and developer of the IDEA protocolIDEA: Investigate, Discuss, Estimate, Aggregate — a structured protocol designed to extract calibrated expert judgements and combine them while minimising anchoring, groupthink, and overconfidence. See: Hanea et al. (2021), Risk Analysis., recommends this order to avoid anchoring and overconfidence when forming a credible interval:
- Lower bound first (your p10): Think of all the reasons this value might be small — technological breakthroughs, optimistic scenarios, best-case conditions. What is a plausible floor? This is the number below which you assign only a 1-in-10 chance of the true value falling.
- Upper bound second (your p90): Think of all the reasons this value might be large — setbacks, unexpected hurdles, worst-case scenarios. This is the number above which you assign only a 1-in-10 chance.
- Median last: Having fully engaged with both extremes, find your balance point — the value for which you judge an even chance that the true outcome is above or below.
Starting with the median and adding bounds afterwards tends to produce intervals that are too narrow (anchoring + overconfidence). When forming each bound, ask: "What factors could drive this much higher or lower — and how variable are those factors?" Fold that variability into the bounds. If there are things you genuinely don't know, fold that epistemic uncertainty in too — wider bounds are the honest reflection of your state of knowledge.
This form is a lightweight structured survey — not a formal expert elicitation protocol.
Cost basis: 2025 US dollars per kg of undifferentiated cultivated-chicken cell biomass, wet weight at harvest. Cost and price estimates refer to production-weighted industry averages, real or hypothetical as specified. Include annualized capital and operating costs; exclude downstream processing, packaging, distribution, and retail margins. Qualifying scale: at least 2,000 metric tonnes per plant per calendar year (2 kt/year). A1 includes hypothetical production; A2 conditions on actual qualifying production.
Full definitions and accounting boundaries
All questions below use these definitions. Click any item to expand. Unless stated otherwise, all values are in inflation-adjusted (CPI) 2025 US dollars, the focal year is calendar year 2036; the near-term questions concern calendar year 2027, and quantities are measured for undifferentiated cultured chicken cell biomass on a wet-weight, at-harvest basis.
▸ Cultured (chicken) meat & the "before any mixture" basis (unfold)
Cultured chicken cell biomass: Undifferentiated (proliferating — actively dividing, in the bioreactor scale-up phase before any directed differentiation into muscle, fat, or connective tissue) chicken cell mass produced in bioreactors, measured before any blending with plant-based or other non-cellular ingredients, and before texturization or downstream structuring. This is the chicken-imitating cultured product in its pre-formulation form.
Before any mixture with plant products: animal cells are often later mixed with plant-based inputs (hydrolysates, plant protein) to reduce total product cost. We focus on the pure cell-biomass cost because it is (1) the technically challenging and costly component, and (2) the quantity most published TEAs estimate; blended product costs can be derived from it given a mixing ratio and filler cost. The cost questions use harvested wet cell biomass. Conventional edible chicken has a different moisture and composition basis; the comparison in C is a production-cost benchmark, not finished-product or retail parity.
Scaffold assumption: assume harvested biomass contains minimal non-degraded scaffolding (<10% w/w). If your estimate assumes scaffold-based production, note it and base your cost on the cellular fraction only.
Why chicken? Among cultured meat products, chicken has the highest stakes for animal welfare. Forecasters may base estimates on bovine or generic-mammal TEAs and explain their conversion method.
▸ Average Production Cost (AC) (unfold)
Average Production Cost (AC) = (Annualized capital charge + all operating costs) ÷ annual kilograms of cultured chicken cell biomass (wet weight, at harvest).
- Capital charge: total capital investment (bioreactors, facility) amortized over plant life via the Capital Recovery Factor, adjusted for financing costs (WACC).
- Operating costs include: basal media (amino acids, glucose, vitamins, buffers), recombinant growth factors, utilities, consumables, labor, maintenance, and plant overhead.
Does not include: downstream scaffolding for structuring; texturization; blending with plant-based or other non-cellular ingredients; packaging; distribution; retail markups; R&D amortization; regulatory approval costs; marketing; or profit above capital costs.
Why average production cost? Competitive markets drive prices toward the minimum of the long-run average total cost curve. An industry average is total relevant production costs divided by total relevant output. Your median is your 50th-percentile estimate of that industry average, across the outcomes specified by each question. For hypothetical production, explain the envisaged mix of plants and output weights.
▸ Wet weight, at harvest & undifferentiated cell biomass (unfold)
Wet weight, at harvest: the mass of cells as harvested from the bioreactor (after separation from spent media, before any further processing), including water — typically ~75–90% water depending on cell line, density, and post-harvest dewatering. We use 80% as our reference assumption. If your estimate assumes a different hydration, please note it in your reasoning.
Undifferentiated cell biomass: proliferating cell mass prior to any directed differentiation step — what most published TEAs (Humbird 2021, Pasitka et al. 2024, CE Delft 2021) model. Cost estimates for differentiated muscle fibers (structured whole cuts) would typically be higher; these questions focus on the proliferation/scale-up phase.
▸ Large-scale plants, value units & target years (unfold)
Large-scale plants: plants producing at least 2,000 metric tonnes of cultivated-chicken cell biomass during the calendar year (2 kt/year). This is realized output, not announced capacity. A1 includes hypothetical qualifying production if no such plants operate; A2 considers only worlds with actual qualifying production. Sales question D includes plants of every size.
Value units: inflation-adjusted (CPI) 2025 US dollars.
Target years: calendar year 2036 for the main questions; calendar year 2027 for actual production, conditional actual costs, and sales.
2036 retains the long-term horizon from the earlier questions. The 2027 block concerns actual near-term outcomes; it no longer substitutes pilot costs if qualifying production is absent.
▸ How should I think about probability estimates? (unfold)
When we ask for a probability, we mean your best calibrated subjective probability — your honest credence given everything you know. One way to think about it: imagine an ideal research team with unlimited resources and data; what probability would you assign that they would ultimately conclude the statement is true? Avoid anchoring to "0% = impossible" / "100% = certain"; a wide interval is more honest than false precision.