Entomoculture: A Preliminary Techno-Economic Assessment
Bibliographic record
Abstract
Cultured meat, or the practice of growing meat from cell culture, has been experiencing rapid advances in research and technology as the field of biotechnology attempts to answer the call to fight climate change and feed a growing global population. A major hurdle for cell-based meat products entering the market in the near-future is their price. The complex production facilities required to make such products will require advanced bioreactor systems, resources such as energy and water, and a skilled labor force, among other factors. The use of insect cells in this process is hypothesized to address some of these costs due to the characteristics that make them more resilient in cell culture when compared to traditional livestock-derived cells. To address the potential for cost savings by utilizing insect cells in the cultivation of protein-enriched foods, here we utilized a techno-economic assessment model. Three different insect cell lines were used in the model. The results indicate that insect cell lines offer potential to significantly reduce the cost per kilogram of cell cultivated meat, along with further opportunities to optimize production processes through technological advances and scaling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".