Cancer weight of evidence for three lower acrylates: Conclusions and recommendations from an expert panel
Bibliographic record
Abstract
An international panel of experts was engaged to assess the cancer weight of evidence (WOE) for three lower acrylates: methyl acrylate, ethyl acrylate, and 2-ethylhexyl acrylate. The review was structured as a three-round, modified Delphi format, a systematic process for collecting independent and deliberative input from panel members, and it included procedural elements to reduce bias and groupthink. Based upon the available science, the panel concluded: (1) The MOA for point of contact tumors observed in rodent cancer bioassays that is best supported by available data involves increased cell replication by cytotoxicity and regenerative proliferation; (2) The WOE supports a cancer classification of "Not likely to be carcinogenic to humans" a conclusion that is more in line with an IARC classification of Group 3 rather than Group 2 B; (3) Quantitative cancer potency values based on rodent tumor data are not required for these chemicals; and (4) Human health risk assessment for these chemicals should instead rely on non-cancer, precursor endpoints observed at the point of contact (e.g., hyperplasia). The degree of consensus (consensus scores of 0.84-0.91 out of a maximum score of 1) and degree of confidence (7.7-8.7 out of a maximum score of 10) in the WOE conclusions is considered high.
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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 | 0.241 | 0.362 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.019 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.016 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".