Estrogen-like activities in blood cleared for endogenous steroid hormones across European and Inuit populations
Bibliographic record
Abstract
Human exposure to environmental contaminants is ubiquitous and can affect individuals living close to as well as remote from the sources of contaminants. All individuals carry a burden of the lipophilic persistent organic pollutants (POPs) and heavy metals in their body. POPs includes polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs) and certain pesticide residues e.g. dichloro-diphenyl-trichloroethane/dichloro-diphenyl-dichloroethylene (DDT/DDE), toxaphenes, β-hexachlorocyclohexane (β-HCH), chlordanes, hexachlorobenzene, and Mirex. Exposure to POPs elicits a number of species- and tissue-specific toxic responses including effects on the reproductive-, immune- and thyroid system. Study on wildlife populations have documented adverse effects, including reproductive end developmental effects that correlate with exposure to one or more of these endocrine modulating chemicals. Especially the exposure during foetal and early life is critical. Although, no clear cut evidence for adverse endocrine-related human health effects has been obtained, the reasonable suspicion based on wildlife, animal and laboratory studies strengthened the need for further research to address the uncertainty and concern. There are a number of factors that complicate the toxicological assessment. Firstly, it is important to remember that no individual is exposed to a single contaminant but to a complex mixture of contaminants, which is life-long beginning during critical developmental windows.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".