A Test of the Passalacqua Age at Death Estimation Method Using the Sacrum
Bibliographic record
Abstract
A test of the accuracy of the Passalacqua (J Forensic Sci, 5, 2009, 255) sacrum method in a forensic context was performed on a sample of 153 individuals from the J.C.B. Grant Skeletal Collection. The Passalacqua (J Forensic Sci, 5, 2009, 255) method assesses seven traits of the sacrum using a 7-digit coding system. An accuracy of 97.3% was achieved using the Passalacqua (J Forensic Sci, 5, 2009, 255) method to estimate adult skeletal age. On average each age estimate differed by 12.87 years from the known age. The method underestimated the age of individuals by an average of 4.3 years. An intra-observer error of 6.6% suggests that the method can be performed with precision. Correlation and regression analysis found that the sacral traits used in the Passalacqua (J Forensic Sci, 5, 2009, 255) method did not have a strong relationship with age or an ability to strongly predict age. Overall, the method was not practical for use in a forensic context due to the broad age ranges, despite the high accuracy and low intra-observer error.
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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 | 0.045 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".