Wanted: dead or alive? Isotopic analysis (δ<sup>13</sup>C and δ<sup>15</sup>N) of <i>Pygoscelis</i> penguin chick tissues supports opportunistic sampling
Bibliographic record
Abstract
RATIONALE: Physiological stress and starvation have been shown to affect δ(13)C and δ(15)N isotope values and, given that animals often die from starvation, the cause of death may be an important factor to consider in stable isotope analyses of opportunistically collected samples. METHODS: We addressed this issue by comparing tissue stable isotope values of living and deceased Adélie (Pygoscelis adeliae) and Chinstrap Penguin (P. antarctica) chicks collected from the same respective populations. RESULTS: No significant difference was found between living and deceased penguin chick feather, down, and toenail isotope values and both groups displayed similar isotopic trends between tissue types. In addition, similar relationships were observed between both species and across several seasons. Furthermore, sub-dermal adiposity and cause of death (starvation and/or predation) had no significant effect on the δ(13)C and δ(15)N values. CONCLUSIONS: Our findings suggest that tissues from deceased penguins can be isotopically representative of tissues obtained from the living population, despite the cause of death, and support the use of opportunistic sampling in stable isotope analyses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".