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Record W4200413845 · doi:10.1080/00085030.2021.2016205

Using momentum to determine serious bodily injury: an experimental study using pig eyes

2021· article· en· W4200413845 on OpenAlexaffvenueabout
Priscilla Burns, Kimberly Nugent, F. Gaspari, Liam D. Hendrikse

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsOntario Tech University
FundersCentral Marine Fisheries Research InstituteIndian Council of Agricultural Research
KeywordsProjectileImpulse (physics)Momentum (technical analysis)Range (aeronautics)MechanicsPhysicsPoison controlSimulationAeronauticsMedicineEngineeringClassical mechanicsMedical emergencyAerospace engineering

Abstract

fetched live from OpenAlex

According to section 2 of the Criminal Code, a firearm is a barrelled weapon that can discharge a projectile capable of causing serious bodily injury or death to a person. Although not defined in the Criminal Code, serious bodily injury has been accepted in Canadian courts as the “penetration or rupture of an eye”. Classifying air guns may be difficult as they are usually not categorized as a firearm, but some are capable of meeting the criteria of a firearm. In previous studies, velocity and/or energy density were used to define a parameter V50, and a minimum energy density range where penetration may occur. This research project sought to evaluate the momentum of the projectile as a new parameter to determine if an air gun is capable of causing serious bodily injury. Three air guns, with five projectile types, were fired 10 times each into pig eyes. Results indicated that a minimum momentum value may be applied to each projectile of a different shape, regardless of the projectile’s mass. Minimum momentum values ranging from 0.026 kg*m/s (pointed) to 0.039 kg m/s (flat nose) were observed. It is hypothesised that impulse, which considers the cross-sectional area of projectiles, would be a universal parameter and more research should be done to test this.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Society of Forensic Science JournalSame topicTraumatic Ocular and Foreign Body InjuriesFrench-language works237,207