Bibliographic record
Abstract
Over the past 3 decades, in a series of studies on some of the most extensively studied toxic chemicals and pollutants, scientists have found that the amount of toxic chemical linked with the development of a disease or death-which is central to determining "safe" or "hazardous" levels-is proportionately greater at the lowest dose or levels of exposure. These results, which are contrary to the way the United States Environmental Protection Agency (EPA) and other regulatory agencies assess the risk of chemicals, indicate that we have underestimated the impact of toxic chemicals on death and disease. If widely disseminated chemicals and pollutants-like radon, lead, airborne particles, asbestos, tobacco, and benzene-do not exhibit a threshold and are proportionately more toxic at the lowest levels of exposure, we will need to achieve near-zero exposures to protect public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.026 | 0.048 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".