A City‐wide Investigation of the Isotopic Distribution and Source of Tap Waters for Forensic Human Geolocation Ground‐truthing
Bibliographic record
Abstract
Abstract Human geolocation is prefaced on the accuracy of the geographic precision of mapped isotopic values for drinking water. As most people live in cities, it becomes important to understand city water supplies and how the isotopic values uniquely reflect that city. This study investigated the isotopic distribution of δ 2 H and δ 18 O from sourced tap waters that were collected from across the Metro Vancouver ( MV ) area ( n = 135). The results revealed that the isotopic values reflect their water sources with a range of 5.3‰ for δ 18 O tap and 29.3‰ for δ 2 H tap for MV . The results indicate that individual cities need higher resolution studies to determine their tap water isotopic ranges, and a good understanding of the water supply network itself for human geolocation work. With an extended high‐resolution understanding of each city, human tissue may be compared with more certainty for geolocation.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".