Strontium and Oxygen Isotope Profiles of Sequentially Sampled Modern Bison (<i>Bison bison bison</i>) Teeth from Interior Alaska as Proxies of Seasonal Mobility
Bibliographic record
Abstract
Studies addressing prehistoric mobility in animals typically use isotopic analyses of sequentially formed tissues, such as the growth layers in teeth, to infer physical movement on the landscape. Strontium isotope ratios (87Sr/86Sr values), which vary geographically, are particularly useful for this purpose, especially when paired with stable oxygen isotope ratios (δ18O), which vary seasonally. Together, these two isotope systems can provide information about past animal movement patterns on a seasonal scale. However, while many studies have used 87Sr/86Sr and δ18O values from analyses of sequentially formed tissues for this purpose, there have been limited analyses on modern animals of known movement patterns across high-latitude regions. In this pilot study, we sequentially sampled and analyzed one second molar (M2) and two third molars (M3) from two bison (Bison bison bison) from the Delta bison herd, which resides in interior Alaska and has known and documented seasonal mobility patterns. The resulting 87Sr/86Sr values from the teeth were compared to a high-resolution 87Sr/86Sr isoscape for the region and were paired with δ18O analyses to determine whether the seasonal 87Sr/86Sr values matched the predicted values for each of the seasonal bison habitat areas. The results indicate that the 87Sr/86Sr and δ18O values reliably reflected the known seasonal mobility patterns of bison and suggest that this approach could be used to investigate the mobility patterns of prehistoric bison in Alaska and surrounding high-latitude regions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".