Stable‐hydrogen isotope heterogeneity in keratinous materials: mass spectrometry and migratory wildlife tissue subsampling strategies
Why this work is in the frame
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Bibliographic record
Abstract
Stable-hydrogen isotope measurements (deltaD) of biological tissues have gained widespread acceptance in wildlife and forensic studies, especially in tracking geographical movements of birds and other species. Continuous-flow isotope-ratio mass spectrometry enables high-throughput deltaD analyses to be conducted on tissue samples as small as 0.15 mg, compared with conventional offline analyses that require 7-10 mg. This reduction in sample size has raised concerns regarding intra-sample hydrogen isotopic variance due to potential biological heterogeneities that could exceed interpretations of geospatial origin. To help resolve this, feathers were obtained from captive birds to examine isotopic variance expected due to sample size, location, and heterogeneity factors, and from selected wild birds to examine isotopic variance due to these and to additional dietary or location changes during feather growth. Captive bird feathers were sub-sampled along the vane on either side of a single feather at masses of 0.25, 0.35, 0.45, 0.6, 1.0 and 2.0 mg, and along the rachis. The results showed consistency of feather deltaD measurements across a wide range of sample masses. Within-feather deltaD isotopic variance for captive and some wild birds was as low as +/-3 per thousand for vane material, which corresponds to a geospatial resolution of about 1 degree of latitude in central North America. Intra-sample variance for the rachis was +/-5 per thousand, with lower deltaD values for both wild and captive birds. However, given the extraordinary intra-feather deltaD variance observed in some wild species, we recommend researchers first carefully assess the degree of intra- and inter-sample hydrogen isotopic variation in the selected tissue growth period for the species of interest before geospatial interpretations of origin are attempted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it