Fragmentation characteristics of long bones resulting from impact of different ammunition sizes
Bibliographic record
Abstract
Abstract Firearm violence has continued to increase, yet there remains a gap in the literature surrounding GSW fracture patterns to long bones. The majority of GSW research is centered on the cranium or thoracic bones, as they are most affiliated with fatal injuries. The present study examined differences in fragmentation and trauma characteristics on long bones caused by two ammunition types. White‐tailed deer ( Odocoileus virginianus ) tibiae ( n = 50) were encased in 10% ballistic gelatin, and 9 mm ammunition from a handgun and 5.56 mm ammunition from an assault rifle were fired from 3 yards (~2.74 m). Due to the higher potential wounding energy, it was anticipated that tibiae impacted by 5.56 mm ammunition would exhibit a greater degree of fragmentation and obscure fracture patterns. Conversely, fragmentation patterns from 9 mm ammunition were expected to be more discernible, given the lower energy transfer and smaller caliber, allowing for easier classification of fracture patterns. A Mann–Whitney U ‐test revealed 5.56 mm ammunition caused more fragmentation than 9 mm ( p = 0.002). False butterfly fractures were observed in 48% of the 9 mm sample and 4% of the 5.56 mm sample. Chi‐square tests for independence showed that all but stepped breakout ( χ 2 [1] = 1.299, p = 0.254) had a statistical association with an ammunition type. The present study found significant differences between the frequency of observed ballistic characteristics and ammunition type within the sample; however, due to similarities, it is not recommended to use fracture pattern analysis as a method of classifying ammunition type.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".