Reconstruction of pinniped diets: accounting for complete digestion of otoliths and cephalopod beaks
Bibliographic record
Abstract
The recovery of sagittal fish otoliths and cephalopod beaks from fecal samples is an important source of information about the diets of marine mammals. Nevertheless, diet reconstructions are biased to some extent because of the partial and complete digestion of these prey structures. Although some authors have used correction factors to account for partial digestion of otoliths, none to date have corrected for the number of otoliths and cephalopod beaks that are completely digested, termed number correction factors (NCFs). Data from nine studies of captive pinnipeds show that corrections for the complete digestion of otoliths and cephalopod beaks range from 1.0 to 25.0 in the 28 prey species. Correction factors ranged from 1.0 to 10.0 in cases where seals could exercise by swimming during the experiment. In several species, NCFs vary inversely with prey length. The effect of applying NCFs will depend on the relative proportion of prey species in the diet and the NCFs of these species. Nevertheless, estimates of the species composition of marine mammal diets will benefit from the use of NCFs. Finally, standardization of experimental protocols and attention to the estimation of variability are needed to provide more reliable NCFs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".