Bibliographic record
Abstract
Quantifying the amount of cortical bone loss is one variable used in histological methods of adult age estimation. Measurements of cortical area tend to be subjective and additional information regarding bone loss is not captured considering cancellous bone is disregarded. We describe whether measuring bone area (cancellous + cortical area) rather than cortical area may improve histological age estimation for the sixth rib. Mid-shaft rib cross-sections (n = 114) with a skewed sex distribution were analyzed. Ages range from 16 to 87 years. Variables included: total cross-sectional area, cortical area, bone area, relative bone area, relative cortical area, and endosteal area. Males have larger mean total cross-sectional area, bone area, and cortical area than females. Females display a larger mean endosteal area and greater mean relative measure values. Relative bone area significantly correlates with age. The relative bone area variable will provide researchers with a less subjective and more accurate measure than cortical area.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".