Strontium isotope ratios of human hair from the United States: Patterns and aberrations
Bibliographic record
Abstract
Rationale Strontium isotope ratios ( 87 Sr/ 86 Sr) of hair may be a valuable tool to estimate human provenance. However, the systematics and mechanisms controlling spatial variation in 87 Sr/ 86 Sr of modern human hair remain unclear. Here, we measure 87 Sr/ 86 Sr of hair specimens from across the USA to assess the presence of geospatial relationships. Methods Ninety‐eight human hair specimens were collected from salon/barbershop floors in 48 municipalities throughout the conterminous USA. [Sr] and 87 Sr/ 86 Sr ratios were measured from hair using quadrupole and multi‐collector inductively coupled plasma mass spectrometers, respectively. The [Sr] and 87 Sr/ 86 Sr ratios of hair were compared with the measured [Sr] and 87 Sr/ 86 Sr ratios of tap waters from the collection locations. In addition, the 87 Sr/ 86 Sr ratio of hair was compared with the modeled ratios of bedrock and surface waters. Results Hair color was independent of the 87 Sr/ 86 Sr ratio, but related to [Sr]. The 87 Sr/ 86 Sr ratios of hair and leachate were not statistically different and were positively correlated; however, in several hair‐leachate pairs, the ratios were conspicuously different. The 87 Sr/ 86 Sr ratios of both hair and leachate were linearly correlated with tap water. The 87 Sr/ 86 Sr ratio of hair was also significantly correlated with the modeled ratio of bedrock and surface waters, although the 87 Sr/ 86 Sr ratio of hair was most strongly correlated with the measured ratio of tap water. Conclusions The 87 Sr/ 86 Sr ratio of hair is related to the ratio of tap water, which varied geographically. The ratio of hair provided geographic information about an individual's recent residence. Differences in the 87 Sr/ 86 Sr ratios of hair and hair leachate may be concomitant with travel and could potentially be used as a screening tool to identify recent movements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".