Bibliographic record
Abstract
The human first rib is relatively easy to identify and is often preserved, in comparison with elements such as the fourth rib and pubic symphysis. Therefore it is potentially a valuable skeletal element for estimating age in forensic and archaeological contexts. A method of adult age estimation using the first rib (Kunos et al., 1999) is tested on a sample of known age skeletons from the J.C.B. Grant Collection (n = 29, mean age = 55.7 years). The high correlation coefficient (r = 0.69) and moderate coefficient of determination (r2 = 0.47) demonstrate agreement between the known and estimated ages, suggesting that the first rib demonstates morphological changes with age. The inaccuracy and bias are high (all ages inaccuracy = 10.4 years, bias = 4.7 years) but comparable to several other age estimation methods in common use. Although the results are not as good for younger age categories (< 50 years: inaccuracy and bias rank ninth of nine age estimation methods), the inaccuracy and bias for the older age categories are relatively low (60 + years inaccuracy = 8.9 years, ranks third out of nine; bias = − 5.8 years, ranks first out of nine) compared with other age estimation methods. The first rib method is reasonably precise (93% of individuals fall within the limits of agreement of the mean difference between two trials). The first rib method is therefore a useful addition to the methods available for biological profile reconstructions from skeletal remains, especially if it is suspected that the remains represent an older individual. Copyright © 2005 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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 | 0.011 |
| 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".