An introduction to the sources, fate, occurrence and effects of endocrine disrupting chemicals released into the environment
Bibliographic record
Abstract
Many classes of compounds are known or suspected to disrupt the endocrine system of vertebrate and invertebrate organisms. This review of the sources and fate of selected endocrine disrupting chemicals (EDCs) in the environment includes classes of compounds that are "legacy" contaminants, as well as contaminants of emerging concern. EDCs included for discussion are organochlorine compounds, halogenated aromatic hydrocarbons, brominated flame retardants, per- and polyfluoroalkyl substances, alkylphenols, phthalates, bisphenol A and analogues, pharmaceuticals, drugs of abuse and steroid hormones, personal care products, and organotins. An exhaustive survey of the fate of these contaminants in all environmental media (e.g., air, water, soil, biota, foods and beverages) is beyond the scope of this review, so the priority is to highlight the fate of EDCs in environmental media for which there is a clear link between exposure and endocrine effects in humans or in biota from other taxa. Where appropriate, linkages are also made between the fate of EDCs and regulatory limits such as environmental quality guidelines for water and sediments and total daily intake values for 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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".