Composition of Beached Marine Birds from an Oiling Event in Southeastern Newfoundland
Bibliographic record
Abstract
The waters off Newfoundland and Labrador, Canada, have one of the worst chronic oiling problems in the world.Although the species generally affected by chronic oiling is known, details on the sex, age and condition of birds killed are not well understood.In late November 2004, oiled seabirds began arriving on the beaches of eastern Placentia Bay.Over the next week, 409 oiled marine birds were collected, with Thick-billed Murres Uria lomvia (67%) and Dovekies Alle alle (23%) constituting the majority.Adult birds comprised 80% (n = 253) of Thick-billed Murres, 61% (n = 84) of Dovekies and only 38% (n = 16) of Common Murres Uria aalge.Sex ratios were close to unity (48.2% male, n = 189) for Thick-billed Murres, but male-biased for Dovekies (60.5%, n = 76) and Common Murres (85.7%, n = 14).Most Dovekies and Thick-billed Murres were found dead (83%), with the highest proportion found alive three and four days, respectively, after the first birds arrived.In spite of additional mass from the oil, body masses of Thick-billed Murres were low (mean: 742 g; range: 520-986 g; versus an expected 950 g for wintering birds).This study confirms previous assumptions that chronic oil pollution in Newfoundland affects all ages of Thick-billed Murres equally, because the age distribution among recovered birds was similar to that expected in the population at large.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".