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Record W2913925270 · doi:10.1111/1556-4029.14004

Bullet Caliber and Type Categorization from Gunshot Wounds in<i>Sus Scrofa</i>(Linnaeus) Long Bone

2019· article· en· W2913925270 on OpenAlexaff
Bailey J. Henwood, Tracy S. Oost, Scott I. Fairgrieve

Bibliographic record

VenueJournal of Forensic Sciences · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsLaurentian University
Fundersnot available
KeywordsCaliberShot (pellet)RifleShouldersAnatomyPoison controlForensic anthropologyMedicineSurgeryMaterials scienceArchaeologyMedical emergencyGeography

Abstract

fetched live from OpenAlex

Studies on ballistic trauma to the ribs and thorax, cranium, and long bones demonstrate the potential of obtaining a bullet caliber from an entrance wound. In order to validate prior research on caliber estimation in bone tissue and assess the viability of bullet type determination based on the macroscopic evidence at the entrance wound, thirty fleshed pork (Sus scrofa) shoulders (humeri) were shot with either lead or copper jacketed bullets in one of three calibers; 0.22, 9 mm, or 0.38. Overall, our findings are consistent with previous research indicating that calibers can be grouped into "small" and "large" categories. Bullet type, lead or copper jacket, can be ascertained based on cortical flaking and the analysis of materials deposited around the entry wound. The addition of this evidence holds value in cases where no firearm or ballistic evidence is recovered from a crime scene.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.258
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2019
Admission routes1
Has abstractyes

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