Shotgun slug wads as a marker of range of fire: A case report and novel firearm testing data
Bibliographic record
Abstract
Assessment of wound characteristics and the identification of various constituents of firearm discharge at autopsy play a key role in the determination of range of fire. In relation to wounds caused by shotguns, identification of the wad within the wound track, or of injury caused by the wad, is typically thought to suggest a fairly close range of fire. We present a case of a fatality due to a shotgun slug wound where the presence of the wad within the decedent's body was proposed by defense at criminal trial to favor accidental close range discharge during a struggle for the weapon-as opposed to the prosecution's contention of intentional firing of the weapon from a greater range and through an intermediate target. We undertook test firing of a shotgun of similar design to that which was fired during the interaction (a 12-gauge pump-action shotgun) using shotshells consistent with the slug that was recovered from the body (Winchester Super X brand), which demonstrated that the non-attached fiber wad present in this shotshell design can accompany the slug over distances of at least up to 22 feet (6.7 m) and even after transit through intermediate targets such as a vehicle headrest. These novel data provide assistance with estimation of range of fire in instances of injuries caused by shotgun slugs.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".