Influence of in ovo mercury exposure, lake acidity, and other factors on common loon egg and chick quality in Wisconsin
Bibliographic record
Abstract
A field study was conducted in Wisconsin (USA) to characterize in ovo mercury (Hg) exposure in common loons (Gavia immer). Total Hg mass fractions ranged from 0.17 µg/g to 1.23 µg/g wet weight in eggs collected from nests on lakes representing a wide range of pH (5.0-8.1) and were modeled as a function of maternal loon Hg exposure and egg laying order. Blood total Hg mass fractions in a sample of loon chicks ranged from 0.84 µg/g to 3.86 µg/g wet weight at hatch. Factors other than mercury exposure that may have persistent consequences on development of chicks from eggs collected on low-pH lakes (i.e., egg selenium, calcium, and fatty acid mass fractions) do not seem to be contributing to reported differences in loon chick quality as a function of lake pH. However, it was observed that adult male loons holding territories on neutral-pH lakes were larger on average than those occupying territories on low-pH lakes. Differences in adult body size of common loons holding territories on neutral-versus low-pH lakes may have genetic implications for differences in lake-source-related quality (i.e., size) in chicks. The tendency for high in ovo Hg exposure and smaller adult male size to co-occur in low-pH lakes complicates the interpretation of the relative contributions of each to resulting chick quality.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".