A Test of Hartnett's Revisions to the Pubic Symphysis and Fourth Rib Methods on a Modern Sample
Bibliographic record
Abstract
Estimating age at death is one of the most important aspects of creating a biological profile. Most adult age estimation methods were developed on North American skeletal collections from the early to mid-20th century, and their applicability to modern populations has been questioned. In 2010, Hartnett used a modern skeletal collection from the Maricopia County Forensic Science Centre to revise the Suchey-Brooks pubic symphysis method and the İşcan et al. fourth rib methods. The current study tests Hartnett's revised methods as well as the original Suchey-Brooks and İşcan et al. methods on a modern sample from the William Bass Skeletal Collection (N = 313, mean age = 58.5, range 19-92). Results show that the Suchey-Brooks and İşcan et al. methods assign individuals to the correct phase 70.8% and 57.5% of the time compared with Hartnett's revised methods at 58.1% and 29.7%, respectively, with correctness scores based on one standard deviation of the mean rather than the entire age range. Accuracy and bias scores are significantly improved for Hartnett's revised pubic symphysis method and marginally better for Hartnett's revised fourth rib method, suggesting that the revised mean ages at death of Hartnett's phases better reflect this modern population. Overall, both Hartnett's revised methods are reliable age estimation methods. For the pubic symphysis, there are significant improvements in accuracy and bias scores, especially for older individuals; however, for the fourth rib, the results are comparable to the original İşcan et al. methods, with some improvement for older individuals.
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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 | 0.127 | 0.379 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".