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Record W3190596418 · doi:10.1038/s41598-021-95153-w

Assessing the predictability of existing water-to-enamel geolocation models against known human teeth

2021· article· en· W3190596418 on OpenAlexafffundabout
Momoko Ueda, Lynne Bell

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSimon Fraser University
FundersBritish Columbia Knowledge Development FundSocial Sciences and Humanities Research Council of CanadaUniversity of Cape TownSimon Fraser UniversityUniversity of WaterlooCanada Foundation for Innovation
KeywordsPredictabilityGeolocationEnamel paintComputer scienceDentistryWorld Wide WebMedicineStatisticsMathematics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.014
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.100
GPT teacher head0.332
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2021
Admission routes3
Has abstractyes

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