Radiography of Perforating Centerfire Rifle Wounds of the Trunk
Bibliographic record
Abstract
All deaths resulting from perforating centerfire rifle wounds of the chest and abdomen, investigated by the Office of the Chief Medical Examiner for the Province of Alberta from 1988 to 1995. were reviewed retrospectively to determine whether the radiographic distribution of bullet fragments in such cases is a useful predictor of bullet trajectory. Study cases were limited to single gunshot wounds without surgical intervention or intermediate targets, and for which adequate radiography was available. Three pathologists individually viewed the radiographs on two separate occasions; wound locations were provided for the second viewing (Group 2). Differences in opinion regarding direction of fire were resolved by consensus review. A trauma radiologist independently made two sets of interpretations in the same way. Comparisons of these groups of interpretations were made with the actual bullet direction determined at autopsy. Of 21 cases included in the study, only three (14.3%) did not require consensus resolution in either group. Accuracy of pathologists' interpretation improved from 38.1% (8/21) to 76.2% (16/21) with provision of wound locations (p = 0.012). The radiologist achieved similar improvement, from 28.6% (6/21) to 47.6% (10/21). The rate of agreement between radiologist and pathologists increased from 42.9% (9/21) to 61.9% (13/21) between Groups 1 and 2. Both the pathologists and radiologist interpreted several cases the same way in both groups; of those cases interpreted differently, the second interpretation was occasionally incorrect after correct interpretation in Group 1. We conclude that bullet direction for perforating centerfire rifle wounds cannot be accurately determined from postmortem radiographs. When wound location is known, the ability to predict bullet direction improves but is still subject to error, including a lack of consistency between observers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".