Paleoepidemiology of vertebral degenerative disease in a Pre‐Columbian Muisca series from Colombia
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".