Bibliographic record
Abstract
In response to our article “Pesticide assessment: Protecting public health on the home turf”, the Industry Task Force II on 2,4-D Research Data asserts that Canada's risk assessment led to “incredible (sic) confidence … that 2,4-D does not pose a risk to human health.” To put this opinion in perspective, the Task Force consortium owns the registrations for the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), and funds and circulates research studies to government agencies, including to Canada's Pest Management Regulatory Agency (PMRA). The Task Force contends that 2,4-D does not pose a cancer risk, but Canada's and other cited government agencies found that the evidence was inconclusive. This is not the same as risk-free. Recent writings of Gandhi and Alavanja (1,2), authors cited by the Task Force, also diverge from the risk-free message. Gandhi published a fact sheet indicating that 2,4-D may be linked to breast cancer via mechanisms other than mutagenesis, such as hormonal effects. Indeed, 2,4-D exhibits estrogenic and androgenic effects in vitro. Endocrine effects were not considered in the 2,4-D reassessment.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.022 | 0.014 |
| Insufficient payload (model declined to judge) | 0.191 | 0.112 |
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".