Multiple stable isotope ( <sup>18</sup> O, <sup>13</sup> C, <sup>15</sup> N and <sup>34</sup> S) analysis of human hair to identify the recent migrants in a rural community in SW England
Bibliographic record
Abstract
Relationships between recent migration and hair delta(18)O values were examined for 40 people living in a rural community in SW England. The isotopic contents of 35 'local' hair samples were compared with those of 5 recently arrived individuals (from Australia, Canada, Chile, Germany and the USA). The hair delta(18)O values of these 'visitors' were +7.9 (Omaha, USA), +11.2 (Jena, Germany), +12.1 (Osorno, Chile), +12.6 (Montreal, Canada) and +14.3 per thousand (Adelaide, Australia). The hair value for the USA visitor (+7.9 per thousand) fell outside the range for the 33 local adult residents, +10.5 to +14.3 per thousand (+12.7 +/- 0.8 per thousand). Hair delta(18)O values did not identify the individuals from Adelaide, Montreal and Osorno as 'visitors', but hair delta(13)C or delta(34)S data did. Combining the hair delta(18)O, delta(13)C and delta(34)S values using principal components analysis (two components explained 89% of the overall variation among the 40 subjects) helped to more clearly distinguish European from non-European individuals, indicating the existence of global overall isotope (geo-origin) relationships.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".