A revised method of sexing the human innominate using Phenice's nonmetric traits and statistical methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The traits of the pubis described by Phenice (Am J Phys Anthropol 30 (1969) 297-302) have been used extensively by physical anthropologist for sex estimation. This study investigates all three of Phenice's characteristics in an approach similar to Walker's (Am J Phys Anthropol 136 (2008) 39-50) study using observations from the cranium and mandible. The ventral arc, the subpubic contour, and the medial aspect of the ischio-pubic ramus were scored on a five-point ordinal scale from a sample of 310 adult, left innominates of known ancestry and sex from the Hamann-Todd Human Osteological Collection and the W.M. Bass Donated Skeletal Collection. Four observers with varying levels of experience blindly scored each trait using new descriptions and illustrations adapted from those originally created by Phenice. The scores were then analyzed with ordinal logistic regression. Using all three traits for sex classification, the mean correct classification rate was 94.5% cross-validated for experienced observers. Intra- and interobserver error in trait scoring was low for all three traits and agreement levels ranged from moderate to substantial. Tests of the method on an independent validation sample provided a classification accuracy of 86.2%. This revision of the Phenice (Am J Phys Anthropol 30 (1969) 297-302) technique is a reliable and valid method of sex estimation from the human innominate that meets the Daubert criteria for court admissibility.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.057 |
| 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 it