Assessing the predictability of existing water-to-enamel geolocation models against known human teeth
Bibliographic record
Abstract
Abstract Stable isotope analysis of human tissues has become a valuable tool for mapping human geolocation. This study adds to the existing knowledge of the relationship between oxygen stable isotopes in human enamel and drinking water by presenting enamel oxygen values in clinic-extracted human dental enamel with known provenance. The results from this study indicate that the theoretical isotopic relationship between enamel and drinking water oxygen is weak at the city and country-level. Differences of up to 15‰ were observed between predicted drinking water oxygen values using existing models and observed values, highlighting the complexity of using water/enamel conversion equations. The lower isotopic boundary of enamel oxygen values is now understood for Metro Vancouver at δ 18 O c(VPDB) = – 11.0‰ and presents the possibility of using stable isotope analysis as an exclusionary tool where individuals falling below threshold value can be identified as non-local. Overall, this study’s results support the development of geographical reference maps for human enamel oxygen.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".