Derivation of screening benchmarks for dietary methylmercury exposure for the common loon (<i>Gavia immer</i>): Rationale for use in ecological risk assessment
Bibliographic record
Abstract
The current understanding of methylmercury (MeHg) toxicity to avian species has improved considerably in recent years and indicates that exposure to environmentally relevant concentrations of MeHg through the diet can adversely affect various aspects of avian health, reproduction, and survival. Because fish-eating birds are at particular risk for elevated MeHg exposure, the authors surveyed the available primary and secondary literature to summarize the effects of dietary MeHg on the common loon (Gavia immer) and to derive ecologically relevant toxic thresholds for dietary exposure to MeHg in fish prey. After considering the available data, the authors propose three screening benchmarks of 0.1, 0.18, and 0.4 µg g(-1) wet weight MeHg in prey fish. The lowest benchmark (0.1 µg g(-1) wet wt) is the threshold for adverse behavioral impacts in adult loons and is close to the empirically determined no observed adverse effects level for subclinical effects observed in captive loon chicks. The remaining benchmarks (0.18 and 0.4 µg g(-1) wet wt) correspond to MeHg levels in prey fish associated with significant reproductive impairment and reproductive failure in wild adult loons. Overall, these benchmarks incorporate recent findings and reviews of MeHg toxicity in aquatic fish-eating birds and provide the basis for a national ecological risk assessment for Hg and loons in Canada.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".