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Effects of Decomposition on Gunshot Wound Characteristics: Under Cold Temperatures with No Insect Activity

2009· article· en· W4245756043 on OpenAlexaffabout
Lauren E. MacAulay, Darryl G. Barr, D.B. Strongman

Bibliographic record

VenueJournal of Forensic Sciences · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsSaint Mary's UniversityRoyal Canadian Mounted Police
Fundersnot available
KeywordsGunshot woundNova scotiaPoison controlGUNSHOT INJURYDecompositionSnowShot (pellet)MedicineSurgeryEnvironmental scienceEcologyMedical emergencyMaterials scienceMeteorologyBiologyArchaeologyGeographyMetallurgy

Abstract

fetched live from OpenAlex

Information on gunshot wound characteristics has been well documented; however, there is little documented information on the effects of decomposition or environmental conditions on gunshot wound characteristics. This study was conducted in order to determine if decomposition would obscure or alter the physical surface characteristics of gunshot wounds when exposed to a low temperature environment. The study was conducted from November 2005 to January 2006 in Nova Scotia, Canada in forested and exposed environments, with air temperatures between -10 degrees C and +10 degrees C. Pigs were used as human models and were shot six times each at three different ranges (contact, 2.5 cm, and 1.5 m). Gunshot wound characteristics persisted until the wounds were covered with ice and snow, after which changes were observed. The changes were recognized as being unique to the different ranges of gunshots and it was concluded that changes due to decomposition under the conditions tested would not affect the collection and interpretation of gunshot wound evidence.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.183

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2009
Admission routes2
Has abstractyes

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