An Evaluation of the Calce Method for Age Estimation
Bibliographic record
Abstract
The Calce method of skeletal age estimation (Am J Phys Anthropol, 148, 2012 and 11) uses the acetabular surface of the os coxa and was developed using 90 individuals from the J.C.B. Grant Skeletal collection. From this collection, pilot tests using a combined sample size of 55 randomized individuals yielded an accuracy of 54.5%. To eliminate the possible issue of variation within the collection, 30 individuals from those that Calce specifically used were assessed by two analysts. Accuracies of 53.3% and 56.7% were obtained, compared with Calce's reported accuracy of 81% (Am J Phys Anthropol, 148, 2012 and 11). This study also used 30 Japanese individuals from the Nagasaki University modern cadaver collection. Due to the high interobserver error (43.3%) and the low accuracies achieved (40% and 46.7%), the Calce method does not perform well on Japanese samples. The low accuracy of this method in general suggests that the trait descriptions should be refined to assist analysts in properly utilizing the method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".