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Record W1575415217 · doi:10.1002/ajpa.22625

Shape, size, and maturity trajectories of the human ilium

2014· article· en· W1575415217 on OpenAlexaff
Laura A. B. Wilson, Rachel Ives, Hugo F.V. Cardoso, Louise Humphrey

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2014
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsSimon Fraser University
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsSexual dimorphismOntogenyBiologySexual maturityJuvenileShape changeMaturity (psychological)AllometryDivergence (linguistics)Evolutionary biologyAnatomyZoologyEcology

Abstract

fetched live from OpenAlex

Morphological traits of the ilium have consistently been more successful for juvenile sex determination than have techniques applied to other skeletal elements, however relatively little is known about the ontogeny and maturation of size and shape dimorphism in the ilium. We use a geometric morphometric approach to quantitatively separate the ontogeny of size and shape of the ilium, and analyze interpopulation differences in the onset, rate and patterning of sexual dimorphism. We captured the shape of three traits for a total of 191 ilia from Lisbon (Portugal) and London (UK) samples of known age and sex (0-17 years). Our results indicate that a) there is a clear dissociation between the ontogeny of size and shape in males and females, b) the ontogeny of size and shape are each defined by non-linear trajectories that differ between the sexes, c) there are interpopulation differences in ontogenetic shape trajectories, which point to population-specific patterning in the attainment of sexual dimorphism, and d) the rate of shape maturation and size maturation is typically higher for females than males. Male and female shape differences in the ilium are brought about by trajectory divergence. Differences in size and shape maturation between the sexes suggest that maturity may confound our ability to discriminate between the sexes by introducing variation not accounted for in age-based groupings. The accuracy of sex determination methods using the ilium may be improved by the use of different traits for particular age groups, to capture the ontogenetic development of shape in both sexes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.298
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.017
GPT teacher head0.314
Teacher spread0.297 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations57
Published2014
Admission routes1
Has abstractyes

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