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Record W2128699066 · doi:10.1002/ajhb.21185

Cortical bone mass and geometry: Age, sex, and intraskeletal variation in nineteenth‐century Euro‐Canadians

2011· article· en· W2128699066 on OpenAlexaffabout
L. Elizabeth Doyle, Richard A. Lazenby, Susan Pfeiffer

Bibliographic record

VenueAmerican Journal of Human Biology · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Northern British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsFemurDivergence (linguistics)Cortical boneAgeingLinear regressionBody mass indexQuantitative computed tomographyHumBone massDemographyWeight-bearingBiologyAnatomyOrthodonticsMedicineOsteoporosisBone densityInternal medicineMathematicsEndocrinologySurgeryStatistics

Abstract

fetched live from OpenAlex

OBJECTIVES: This study seeks to understand the interaction of cortical bone strength and mass within individuals and across age-groups in male and female adults from a relatively active, long-lived nineteenth-century Euro-Canadian population. METHODS: Strength and relative cortical area are measured in paired femora (weight-bearing elements) and metacarpals (manipulative elements) from 139 adults (M = 82; F = 52). Sex and age patterns are tested using linear multiple regression and analysis of covariance. Intra-individual divergence between femora and metacarpals is quantified using the Pearson residual from regression of femur on metacarpal values. Association of residuals with age is tested with curve estimation, factorial analysis of variance and X(2) tests. RESULTS: Strength is maintained but cortical mass declines with age. In females, the slope of cortical mass against age is steeper in the metacarpal than in the femur. However, the degree of divergence between femur and metacarpal within individuals does not increase clearly with age. CONCLUSIONS: Age change in bone strength is systemically controlled and homeostatic, but change in bone mass may vary with limb-specific mechanical environment, particularly in females. However, the distribution of within-individual divergence between femur and metacarpal values suggests that idiosyncratic factors, rather than age, have the strongest influence on intraskeletal divergence. Attempts to reconstruct skeletal ageing in past populations may benefit from an approach that models whole-bone integrity, rather than bone mass alone, and that represents age-related variation in both weight-bearing and nonweight-bearing sites.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.018
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 head0.020
GPT teacher head0.244
Teacher spread0.225 · 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
Published2011
Admission routes2
Has abstractyes

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