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Record W2729712398 · doi:10.1002/ajpa.23595

Effects of osteoarthritis on age‐at‐death estimates from the human pelvis

2018· article· en· W2729712398 on OpenAlexafffund
Stephanie E. Calce, Helen K. Kurki, Darlene A. Weston, Lisa Gould

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersMichael Smith Health Research BCPublic Health Agency of Canada
KeywordsMedicineAcetabulumAnalysis of variancePelvisOsteoarthritisMiddle ageAge adjustmentPubic symphysisDemographyInternal medicineSurgeryEpidemiologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study examined the degree of error in age-at-death estimates when osteoarthritis (OA) is present in three separate pelvic joint areas: (1) the pubic symphysis, (2) the auricular surface, and (3) the acetabulum from a modern known-age European cemetery sample of adults. MATERIALS AND METHODS: Age-at-death ranged from 17 to 79 years (x̄ =50.9 years; n = 252). OA in the pelvic joints was evaluated using standard ranked categorical scoring. Composite OA scores were derived through principal component analysis. Blind age assessments and all analyses were performed separately by region. Error between adult age groups (young, middle, old) and between OA severity groups (low, middle, high) was evaluated using one-way ANOVAs with post-hoc testing, ordinary least squares regression, and transition analysis with a cumulative probit model. Ages-at-transition were compared with Nphases2. RESULTS: Three significant results emerge. First, OA severity has an effect on the accuracy of age estimates from os coxa joints in this sample. Second, this influence is most significant for different age cohorts in each joint region, demonstrating that varied rates of arthritic trait progression occur between the auricular surface, pubic symphyses, and acetabulum. Third, those with OA appear to be aging faster, a consistent trend among the os coxa regions. CONCLUSIONS: These results have significant consequences for understanding the rate of bone remodeling in relation to disease, aging, and the evaluation of skeletal age indicators.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.883

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 studies0.0010.119
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.283
Teacher spread0.269 · 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

Citations18
Published2018
Admission routes2
Has abstractyes

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