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Record W2033060896 · doi:10.1111/1556-4029.12188

A Method for Estimating Sex Using the Clavicle, Humerus, Radius, and Ulna

2013· article· en· W2033060896 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Forensic Sciences · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Windsor
FundersCore Research for Evolutional Science and Technology
KeywordsUlnaStatisticsClaviclePopulationHumerusSample (material)Confidence intervalStandard errorMathematicsMedicineSurgery

Abstract

fetched live from OpenAlex

Sex estimation from skeletal remains can be an important part of preliminary identification. The best source of information for estimating sex is the pelvis but it is not always available for analysis. For these cases, a probabilistic sex estimation method is presented using combinations of standard and alternative measurements of the clavicle, humerus, radius, and ulna. Various equations are developed that are not population specific and that are applicable in various recovery scenarios. The equations were tested using four independent samples (n > 370), including a forensic sample. Allocation accuracies vary by test sample and equation and are consistently good (87.4-97.5%) except for a sample of very small males that show the extreme effects of poverty and mortality bias. For many of the cases where allocation was incorrect, the probabilistic approach indicated that no confidence should be placed in the incorrect allocation and the unknown should be classified as sex indeterminate.

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.

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 categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

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 studies0.0010.017
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 head0.075
GPT teacher head0.354
Teacher spread0.279 · 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