Assessing Age-Related Morphology of the Pubic Symphysis from Digital Images Versus Direct Observation
Bibliographic record
Abstract
The increasingly global role of a forensic anthropologist necessitates a proper means for archiving evidence for re-examination. Large quantities of evidence can be stored and be made readily accessible through digital imaging. This study focuses on age assessment from digital photographs for personal identity reconstructions. A comparison of 52 Suchey-Brooks scores assigned to digital images and actual bone revealed that age assessment from digital images can be completed with accuracy. Coefficients of concordance imply that there significant agreement between osteological assessment of aging criteria from digital images and direct observation-greater than random change alone (p < 0.05). However, assessments from images should be approached with caution since there are inherent limitations of the naked eye in identifying morphological changes in certain skeletal features, especially where older adults are concerned. Although there is no replacement for a hands-on physical assessment, a digital archive may facilitate the global needs of the forensic anthropologist.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".