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Record W1987450983 · doi:10.1002/ajpa.20762

Paleoepidemiology of vertebral degenerative disease in a Pre‐Columbian Muisca series from Colombia

2008· article· en· W1987450983 on OpenAlexaff
Claudia Mercedes Rojas-Sepúlveda, Yann Ardagna, Olivier Dutour

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVertebral bodyMedicinePaleopathologyJoint (building)Articular surfaceJoint diseasePopulationAnatomyOsteoarthritisPathology

Abstract

fetched live from OpenAlex

Major manifestations of vertebral degenerative joint disease were observed on a Pre-Columbian Muisca series from the Soacha Cemetery (11th to 13th centuries) Colombia, South America. In total, 1,646 vertebrae of 83 individuals were examined. Osteophytes, vertebral body joint surface contour change ("lipping"), and vertebral body pitting were evaluated for each vertebral body. For apophyseal joints, joint surface contour change, pitting, and eburnation were recorded. Two methods of frequency calculation and five for vertebral degenerative disease diagnosis were applied and compared, allowing discussion of methodological considerations. Our study showed that 83% of individuals and 32% of vertebrae were classified as positive when diagnosed by the presence of at least one of the following manifestations: osteophytes, vertebral body joint surface contour change ("lipping"), apophyseal joint surface contour change, or eburnation (method called "Pitting excluded"). No significant differences were found between the sexes. In the youngest cohort (15-30 years), 65% of individuals and 10% of vertebrae exhibit at least one of the previously mentioned manifestations. High prevalences suggest a high level of physical activity beginning in childhood which may have accelerated the aging process in this Pre-Columbian population. Historical data are compatible with this hypothesis.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.989

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 studies0.0000.106
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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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

Citations56
Published2008
Admission routes1
Has abstractyes

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