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Record W2005173908 · doi:10.1097/paf.0b013e31820c2be2

Minimum Velocity Necessary for Nonconventional Projectiles to Penetrate the Eye

2011· article· en· W2005173908 on OpenAlexaffabout
John W. Marshall, Dean B. Dahlstrom, Kramer D. Powley

Bibliographic record

VenueAmerican Journal of Forensic Medicine & Pathology · 2011
Typearticle
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsRoyal Canadian Mounted Police
Fundersnot available
KeywordsProjectilePhysicsOpticsOptometryMedicine

Abstract

fetched live from OpenAlex

To satisfy the Criminal Code of Canada's definition of a firearm, a barreled weapon must be capable of causing serious bodily injury or death to a person. Canadian courts have accepted the forensically established criteria of "penetration or rupture of an eye" as serious bodily injury. The minimal velocity of nonconventional ammunition required to penetrate the eye including airsoft projectiles has yet to be established. To establish minimal threshold requirements for eye penetration, empirical tests were conducted using a variety of airsoft projectiles. Using the data obtained from these tests, and previous research using "air gun" projectiles, an "energy density" parameter was calculated for the minimum penetration threshold of an eye. Airsoft guns capable of achieving velocities in excess of 99 m/s (325 ft/s) using conventional 6-mm airsoft ammunition will satisfy the forensically established criteria of "serious bodily injury." The energy density parameter for typical 6-mm plastic airsoft projectiles is 4.3 to 4.8 J/cm². This calculation also encompasses 4.5-mm steel BBs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.039
GPT teacher head0.317
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Forensic Medicine & PathologySame topicTraumatic Ocular and Foreign Body InjuriesFrench-language works237,207