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Record W2086170665 · doi:10.1002/ajpa.21342

Technical note: Enhancement of Scott's molar wear scoring method

2010· article· en· W2086170665 on OpenAlexaff
Natalie L. Shykoluk, Nancy C. Lovell

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMolarQuadrant (abdomen)OrthodonticsObserver (physics)MathematicsComputer scienceDentistryMedicinePhysicsSurgery

Abstract

fetched live from OpenAlex

A method is described for orienting maxillary and mandibular molars in order to standardize the reporting of wear scores on quadrants of the occlusal surfaces (Scott: Am J Phys Anthropol 51 (1979) 213-217). The method, which was developed on an archeological sample from ancient Mendes, Egypt, further requires that quadrant scores be reported individually and sequentially for each tooth, rather than summed, in order to identify more easily differential and directional wear patterns. Intraobserver and interobserver error was found to be negligible when the appropriate diagrams and instructions were consulted. Thus, observer error does not add further to the potential for error associated with Scott's original scoring method.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.067
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.321
Teacher spread0.308 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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