Contaminant effects on the teleost fish thyroid
Bibliographic record
Abstract
Numerous environmentally relevant chemicals, including polychlorinated hydrocarbons, polycyclic aromatic hydrocarbons, organochlorine pesticides, chlorinated paraffins, organophosphorous pesticides, carbamate pesticides, cyanide compounds, methyl bromide, phenols, ammonia, metals, acid loads, sex steroids, and pharmaceuticals, exert acute or chronic effects on the thyroid cascade in the approximately 40 teleost fish species tested to date. Thyroid endpoints, therefore, serve as biomarkers of exposure to environmental pollutants. However, the mechanisms underlying thyroid changes and their physiological consequences are poorly understood because the thyroid cascade may respond indirectly and it has considerable capacity to compensate for abuses that otherwise would disrupt thyroid hormone homeostasis. Indeed, a xenobiotic-induced change in fish thyroid function has yet to be conclusively causally linked to decreased fitness or survival. Other complications in interpretation arise from the diversity of test conditions employed and the often indiscriminate use of numerous thyroid endpoints. Future work should be directed toward standardizing test conditions and thyroid endpoints and investigating causal links between thyroid changes and fish growth, reproduction, and development. Development may be particularly susceptible to thyroid disruption, and thyroid endpoints appropriate for early life stages need to be applied.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".