Thresholds of adversity and their applicability to endocrine disrupting chemicals
Bibliographic record
Abstract
a hazard-based approach. Presumably this is due to an assumed lack of thresholds for the adverse effects of such substances. Conversely, in other jurisdictions, such as USA, Canada, Australia and Japan, endocrine disruptors (EDs) are regulated using a risk-based approach. As a consequence, in recent years there has been increasing controversy on whether thresholds can be inferred for endocrine-mediated effects. There is concern that the endocrine system is too complex to allow estimation of safe levels of exposure to such chemicals. This brief review aims to evaluate the available scientific evidence in this area and offer a sound and robust conclusion supported by this analysis. It is concluded that there is nothing special or unique about endocrine disruption or greater uncertainties in its assessment compared to other non-genotoxic forms of toxicity to justify adopting a non-threshold approach by default. Biology predicts that thresholds of adversity exist and are the rule for all endpoints, including those arising from endocrine disruption. A threshold approach to the risk assessment of endocrine disrupting chemicals is scientifically justified.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".