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Record W2470649205 · doi:10.1111/1556-4029.13892

A Reappraisal of Developing Deciduous Tooth Length as an Estimate of Age in Human Immature Skeletal Remains

2018· article· en· W2470649205 on OpenAlexaff
Hugo F.V. Cardoso, Julia Meyers, Helen M. Liversidge

Bibliographic record

VenueJournal of Forensic Sciences · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDeciduousDeciduous toothForensic anthropologyDeciduous teethDentistryMedicineBiologyGeographyArchaeologyEcology

Abstract

fetched live from OpenAlex

This study provides an update on a quantitative method for immature age estimation based on postnatal deciduous mandibular tooth length. Two known sex and age skeletal collections from Western Europe were sampled (n = 97). Linear regression models for age estimated were calculated for each individual tooth, each sex, and sex combined sample using classical calibration. Prediction errors, residuals, and percentage of individuals whose real age fell within the 95% prediction interval were calculated. The teeth which develop earlier in life, the incisors and the first molar, showed the greatest precision, while the canine showed the least. This method has greater applicability to archeological skeletons or to children in developing countries than for use in North American or European forensic contexts. The method can be applied to incomplete or poorly preserved remains of unknown sex, particularly when dental radiographs are not an option or when teeth have been removed from the alveolus or crypt.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.035
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 head0.047
GPT teacher head0.355
Teacher spread0.309 · 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 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

Citations13
Published2018
Admission routes1
Has abstractyes

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