Comparison between strip sampling and laser ablation methods to infer seasonal movements from intra-tooth strontium isotopes profiles in migratory caribou
Bibliographic record
Abstract
Abstract Strontium isotopes analysis is a powerful tool in the study of past animal movements, notably the sequential analysis of tooth enamel to reconstruct individual movements in a time-series. Compared to traditional solution analysis, high resolution sampling using laser-ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) has the potential to reflect fine scale mobility. However, the averaging of the 87Sr/86Sr intake during the enamel mineralization process may limit fine scale inferences. We compared solution and LA-MC-ICP-MS 87Sr/86Sr intra-tooth profiles from the second and third molars of 5 caribou from the Western Arctic herd, Alaska. Profiles from both methods showed similar trends, reflecting the seasonal migratory movements, but LA-MC-ICP-MS profiles showed a less damped 87Sr/86Sr signal than solution profiles. Geographic assignments of the profile endmembers to the known summer and winter ranges were consistent between methods and with the expected timing of enamel formation but showed discrepancy at a finer scale. Variations on LA-MC-ICP-MS profiles, consistent with expected seasonal movements, suggested more than an admixture of the endmember values. However, more work in understanding enamel formation in Rangifer, and other ungulates, and how 87Sr/86Sr daily intake translates into enamel are needed to assess the real resolution that can be achieved with LA-MC-ICP-MS.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".