Toward Less Confusing Terminology in Endocrine Disruptor Research
Bibliographic record
Abstract
The realization that environmental contaminants interact with hormone receptors and mimic or antagonize the actions of endogenous hormones led to introduction of terms such as endocrine disruptor, endocrine disrupter, hormonally active chemicals, and hormone mimics into the scientific and lay press. Reports suggesting a link between exposure to chemicals adversely affecting the endocrine system and (1) increasing rates of hormone-dependent cancers (breast, prostate, and testicular), (2) developmental detrimental effects in the male reproductive tract, (3) falling sperm counts, and (4) endometriosis resulted in an explosion of research, regulatory actions, and policy changes aimed at better understanding the hazards posed by these chemicals with subsequent restriction in their use. With increasing concern, there is worldwide action to develop testing strategies to allow for early identification of chemicals possessing endocrine disruptor activity. However, despite an expanding literature and numerous expert panel meetings, there continues to be controversy surrounding how to best define endocrine disruptors, resulting in (1) ambiguous use of the term, (2) confusion in the literature, and (3) publication of contentious lists of chemicals purported to be endocrine disruptors. Herein it is argued in favor of a more restrictive definition with adoption of a less ambiguous term, and in favor of development of a classification system to enhance more effective communication and facilitate appropriate allocation of limited resources in this highly charged area of toxicology.
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 | 0.132 | 0.120 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.024 | 0.026 |
| Science and technology studies | 0.007 | 0.069 |
| Scholarly communication | 0.023 | 0.029 |
| Open science | 0.011 | 0.012 |
| Research integrity | 0.011 | 0.033 |
| Insufficient payload (model declined to judge) | 0.002 | 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".