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Record W2906961840 · doi:10.26575/daj.v16i3.155

Metric Analysis of Permanent and Deciduous Teeth from Bronze Age Tell Leilan, Syria

2018· article· en· W2906961840 on OpenAlexafffund
Scott D. Haddow, Nancy C. Lovell

Bibliographic record

VenueDental Anthropology Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsPermanent teethDeciduousCrown (dentistry)Bronze AgeArchaeologyMesopotamiaDeciduous teethGeographyPopulationDentistryDemographyBiologyMedicineEcology

Abstract

fetched live from OpenAlex

Between 1979 and 1989 the skeletal remains of 21 adults and 38 children, yielding 317 permanent and 134 deciduous teeth, were recovered at Tell Leilan, Syria, the site of a major urban center during the emergence of complex state society in northern Mesopotamia in the mid-third millennium BC. Tooth crown dimensions (faciolingual and mesiodistal diameters, total crown area, and molar crown area) are presented and the last two serve as the primary units of comparison for a diachronic interpretation of tooth size variation in the ancient Near East. Both permanent and deciduous dental data support the pattern of dental reduction since the Middle Paleolithic that has been documented for Asia and Europe. The total crown areas for the permanent and deciduous dental samples, 1189 mm2 and 497 mm2 respectively, place this archaeological population at the smaller end of the crown area scale for the Near East; smaller in size than nearby Paleolithic and Neolithic populations. Given the paucity of odontological data for this area, this study contributes to the odontometric history of Mesopotamia and as a summary compilation and comparison of previously conducted odontometric work as it relates to the phenomenon of dental reduction within the ancient Near East.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.059
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.024
GPT teacher head0.282
Teacher spread0.258 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
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

Citations11
Published2018
Admission routes2
Has abstractyes

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