Fin‐icky samples: an assessment of shark fin as a source material for stable isotope analysis
Why this work is in the frame
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Bibliographic record
Abstract
Analyzing stable isotopes (SI: δ 15 N and δ 13 C) in a new tissue requires rigorous testing before its general application in examining aspects of animal ecology. Shark fin provides a novel, minor invasive source material, which is important considering the conservation status of many large sharks. Fin, however, is not a single tissue but composed of multiple tissues, primarily skin and cartilage. This may complicate the interpretation of SI, as fin can be sampled from multiple fins and different regions of a fin from an individual. Here, we examined the variation in δ 15 N and δ 13 C with sample location on the anal fin of Caribbean reef sharks ( Carcharhinus perezi ). Values of δ 15 N and δ 13 C were highly correlated across sampling locations indicating that mean population or size class fin SI data would be reliable. At the individual level, large variation in δ 15 N and δ 13 C between anal fin sampling locations indicates that the varying proportional contributions of tissues would complicate individual level analyses. For three pelagic shark species, dorsal fin δ 13 C values were consistently higher than δ 13 C muscle tissue values, identifying tissue‐specific diet discrimination factors. This would confound multiple tissue studies that assume that SI values across tissues will be equal if the animal is in equilibrium with its diet. Proposed sampling protocols for fin material will negate many of these issues, but caution is warranted for comparisons of SI data between shark fin and other tissues or across species until the isotope dynamics of fin have been experimentally validated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it