Utilizing foot bones for estimation of sex: a case study from modern Chilean adults
Bibliographic record
Abstract
The estimation of sex is an important part of building the biological profile for unknown human remains. Many of the bones traditionally used for the estimation of sex are often found fragmented or incomplete in forensic and archaeological cases. The goal of this research is to derive population-specific discriminant functions from the talus, a preservationally favoured bone, for estimation of sex from a contemporary adult Chilean population. Nine parameters were measured from 220 individuals (113 males and 107 females) with age ranges from 15 to 78 years old. All nine tali variables were sexually dimorphic. Population-specific discriminant function equations were generated for use in sex estimation. Overall, the accuracy of sex classification ranged from 64.1% to 79.7% for the univariate analysis, 79.1% to 84.7% for the direct method, and 82.8% for the stepwise method. Comparisons to other populations were made and the results demonstrated the need for population-specific discriminant functions. Overall, the cross-validated accuracies ranged from 50% to 78%. The talus was shown to be useful for sex estimation in the modern Chilean population.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".