Preliminary Assessment of Avian Stomach Oils: A Vector of Contaminants to Chicks and Potential for Diet Analysis and Biomonitoring
Bibliographic record
Abstract
Bird species from the order Procellariiformes or petrels, including the northern fulmar (Fulmarus glacialis), produce high lipid and high energy content stomach oils from the prey they consume, which enables them to exploit distant marine food sources. Stomach oils are also used as a food source for chicks and for defensive purposes. Samples of stomach oils from two Arctic colonies, St. George Island Alaska, USA and Cape Vera, Devon Island Nunavut, Canada, were collected and analyzed for organochlorine contaminants. SigmaPCB concentrations ranged from 13 to 236 ng g(-1) wet weight (ww) and SigmaDDT concentrations from 5 to 158 ng g(-1) ww and were similar in both sites, though differences in chemical signatures were apparent. Stomach oils are a rich energy source; however, they may also provide a higher dose of contaminants per unit energy than the direct consumption of prey items, as illustrated using mass and energy balance calculations to estimate chick exposure to SigmaDDT for hypothetical stomach oil and whole prey diets. The results of this study suggest that stomach oils are an important vector of organochlorine contaminants to chicks and should be considered in future risk assessments of northern fulmars and other species of petrels. To our knowledge this is the first study of stomach oils as an overlooked vector of organochlorine contaminants to chicks and as a potentially valuable medium for dietary analysis and noninvasive biomonitoring both of petrel dietary exposure and of marine contaminant concentrations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".