The Odontology Victim Identification Skill Assessment System*<sup>,†</sup>
Bibliographic record
Abstract
Mass fatality identification efforts involving forensic odontology can involve hundreds of dental volunteers. A literature review was conducted and forensic odontologists and dental educators consulted to identify lessons learned from past mass fatality identification efforts. As a result, the authors propose a skill assessment system, the Odontology Victim Identification Skill Assessment System (OVID-SAS), which details qualifications required to participate on the Antemortem, Postmortem, Ante/Postmortem Comparison, Field, and Shift Leader/Initial Response Teams. For each qualification, specific skills have been identified along with suggested educational pedagogy and skill assessment methods. Courses and assessments can be developed by dental schools, professional associations, or forensic organizations to teach and test for the skills required for dental volunteers to participate on each team. By implementing a system, such as OVID-SAS, forensic odontologists responsible for organizing and managing a forensic odontology mass fatality identification effort will be able to optimally utilize individuals presenting with proven skills.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.033 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".