Bibliographic record
Abstract
In order to confirm the identity of the deceased, 1.7% of the deaths (162 cases) evaluated at the Harris County Medical Examiner's Office during the time period of this study required a forensic dental evaluation. Data were collected and analyzed. The manner of death was ranked in order as follows: 30% homicide; 20% accident of various types other than motor vehicle accidents; 18% motor vehicle accidents; 16% remain undetermined; 9% natural causes; and 7% suicide. The cause of death was: 24% asphyxia, smoke inhalation, or thermal burn injuries; 23% blunt-force trauma; 18% miscellaneous causes of death; 15% undetermined; 13% gun shot wounds; and 7% asphyxia. The condition of the remains were: 38% charred or incinerated; 31% decomposing; 18% skeletal remains; 6% "fresh" or recently deceased; 4% fragmented; and 3% severely beaten or mangled with displacement of the maxillomandibular region, complicating the dental identification procedure. The gender was: 62% male; 34% female; and 4% undetermined. The race was: 55% Caucasian; 19% Hispanic; 14% black; 1% Asian; and 11% undetermined. The age was: 2% from 0 to 10 years of age; 9% from 11 to 20; 21% from 21 to 30; 18% from 31 to 40; 13% from 41 to 50; 8% from 51 to 60; 5% from 61 to 70; 4% from 71 to 80; 1% from 81 to 90; and 19% undetermined. Further evaluation of these and future dental identification cases will provide valuable data to help prepare the forensic dentist for the wide variety of cases that must be evaluated in the course of their careers.
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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 | 0.001 | 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 | 0.001 | 0.021 |
| 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; a candidate call from one teacher head, 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".