Possible dependence of sternum non-metric features on sex, age, and stature from a forensic viewpoint: a study in an Iranian population
Bibliographic record
Abstract
Morphological traits of the sternum are rarely evaluated in forensic studies. This study evaluates these features in sex-, age-, and stature-specific groups. A cross-sectional retrospective study was conducted including 400 chest CT scans from 2020 to 2021 which were categorized based on three factors of sex (N = 400; male and female), age (N = 400; group 1: 20–39 years, group 2: 40–59 years, and group 3: >60 years), and stature (N = 190; group 1: 150–159 cm, group 2: 160–169 cm, group 3: 170–179 cm, and group 4: >180 cm). Non-metric parameters of the manubrium, body of sternum, and xiphoid process were investigated. Sex-related distribution of morphologic features of the manubrium in all of the participants demonstrated a significantly higher presence of the arch-shaped prominence (ASP) in males (N = 212, 94.22%) compared with females (N = 135, 77.14%). Morphologic features of the body of the sternum related to sex in all of participants demonstrated a significantly higher flat body shape (BS) in males (N = 142, 63.4%) compared with females (N = 85, 48.3%), and a significantly lower O shape BS in males (N = 5, 2.23%) compared with females (N = 19, 10.8%). Although non-metric morphological traits of the sternum represent a great variety in different studies, some of the features can be considered as possible factors specific to sex (ASP is higher in males than females), age (denticulate costal incisura is higher in <40 than >40 years), and stature (flat BS is higher in >170 than <170 cm).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".