Examination of relationships between stable isotopes and cortisol concentrations along the length of phocid whiskers
Bibliographic record
Abstract
Abstract Alaskan seals are found in remote and sometimes inaccessible locations, making it difficult to collect time‐series information. This study explores a novel method to examine temporal changes in diet and physiological status of ringed (Pusa hispida), spotted (Phoca largha), and harbor (Phoca vitulina) seals using cortisol concentrations and δ15N and δ13C stable isotopes (SIs) measured in serial sections of whiskers. As whiskers grow, whisker tissue is deposited sequentially making these measurements temporally aligned. Whisker cortisol presented in a distinct pattern with elevated concentrations at the root section followed by a curvilinear decline moving toward the tip of most whiskers. Comparing SIs at the root to the rest of the whiskers, δ13C values were slightly lower in ringed and harbor seal whiskers and δ15N values were slightly higher in harbor seal whiskers. The data were modeled controlling for the observed trends in cortisol concentrations and further associations between cortisol concentrations and SIs were detected in spotted and harbor seal whiskers. Additional research examining the source and stability of whisker cortisol is warranted. However, the methods presented here demonstrate that whiskers could prove valuable to gather long‐term and naturally aligned dietary and physiological information.
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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 | 0.000 | 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".