DNA-Reactive Carcinogens: Mode of Action and Human Cancer Hazard
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It has been known for decades that mutagenicity plays an important role in the activity of most carcinogens. This mutagenicity can result from direct damage to DNA through a chemical being DNA reactive or from indirect effects, such as through the production of oxygen radicals that then react with DNA. This article presents a set of key events whereby DNA reactivity initiates the process of carcinogenicity that leads to the subsequent mutation induction and enhanced cell proliferation that ultimately results in tumor development. This set of key events for DNA-reactive chemicals was applied to two case studies (aflatoxin B1 and dichloromethane) with the aim of assessing the utility of the Human Relevance Framework (HRF) for this class of chemicals. The conclusions were that the HRF was a viable approach for the use of mechanistic data for DNA-reactive chemicals obtained from both laboratory animals and human cells in vivo and in vitro for predicting human carcinogenicity. In the case of aflatoxin B1, the HRF could be used to predict that carcinogenicity in humans was a likely outcome. In contrast, the HRF predicted that the human carcinogenic potential of dichloromethane was at best less likely than in rodents; this conclusion was supported by the available epidemiological data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it