A review of epidemiologic studies of triazine herbicides and cancer
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
This is an update of a previous review of epidemiological evidence pertaining to the human carcinogenic potential of triazine herbicides. In 36 studies evaluated, atrazine was the most common triazine investigated. In general the studies were limited by lack of in-depth exposure measurements and by small numbers of subjects with potential high exposure and/or with many years of follow-up since first exposure. Non-Hodgkin lymphoma, prostate cancer, and breast cancer were most frequently investigated. Only one to three analytical or ecological studies investigated Hodgkin lymphoma, leukemia, multiple myeloma, soft tissue sarcoma, hairy-cell leukemia, melanoma, and cancers of the ovary, testes, colon, stomach, lung, brain, bladder, buccal cavity, and pharynx. Results of these studies were typically imprecise and did not form an adequate basis for determining if triazine exposure causes any form of cancer. Collectively, the available epidemiology studies do not provide consistent, scientifically convincing evidence of a causal relationship between exposure to atrazine or triazine herbicides and cancer in humans. Based upon the assessment studies, there is no scientific basis for inferring the existence of a causal relationship between triazine exposure and the occurrence of cancer in humans.
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.
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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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