Understanding muscle markers: Aggregation and construct validity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Musculoskeletal markers are frequently used to reconstruct past lifestyles and activity patterns. Yet, the reliability of muscle marker measurements has been called into question because they allegedly fail to correlate with cross-sectional properties and exercise patterns, and are confounded by body size. In this study, the principle of aggregation was used to sum muscle markers over 7 insertion sites (4 humeral, 2 radial, and 1 ulnar) and examine the effects on them of body size, age, sex, and cross-sectional properties. Analyses were made of a sample of 91 (66 males, 25 females) Native British Columbians (3500-1500 years BP) and 18th century Quebec prisoners. Muscle markers were measured using three-point observer rating scales; size was measured by standard methods; age and sex were determined through pelvic, cranial, and dental morphology; and cross-sectional properties were calculated from radiographs. Whereas any single muscle marker component failed to correlate with age, size, sex, or cross-sections, aggregate muscle marker correlated with: age, r = 0.49; size, r = 0.38; sex, r = 0.40; and, cross-sections, r = 0.38; P < 0.001. Older individuals had greater muscle markers, as did larger individuals, males, and those with more robust cross-sections. Based on partial correlations and regression analyses, age was the best overall predictor of aggregate muscle marker.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.074 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it