MétaCan
Menu
Back to cohort
Record W1743487016 · doi:10.1111/1556-4029.12940

Evaluation of GLOCK 9 mm Firing Pin Aperture Shear Mark Individuality Based On 1,632 Different Pistols by Traditional Pattern Matching and IBIS Pattern Recognition

2015· article· en· W1743487016 on OpenAlexaff
James E. Hamby, Stephen R. Norris, Nicholas Petraco

Bibliographic record

VenueJournal of Forensic Sciences · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsCartridgeMatching (statistics)IbisPoison controlBallisticsStatisticsEngineeringCrashForensic engineeringSimulationMathematicsComputer scienceProjectileMaterials scienceMechanical engineeringGeology

Abstract

fetched live from OpenAlex

Over a period of 21 years, a number of fired GLOCK cartridge cases have been evaluated. A total of 1632 GLOCK firearms were used to generate a sample of the same size. Our research hypothesis was that no cartridge cases fired from different 9-mm semiautomatic GLOCK pistols would be mistaken as coming from the same gun. Using optical comparison microscopy, two separate experiments were carried out to test this hypothesis. A subsample of 617 test-fired cases were subjected to algorithmic comparison by the Integrated Ballistics Identification System (IBIS). The second experiment subjected the full set of 1632 cases to manual comparisons using traditional pattern matching. None of the cartridge cases were "matched" by either of these two experiments. Using these empirical findings, an established Bayesian probability model was used to estimate the chance that a 9-mm cartridge case, fired from a GLOCK, could be mistaken as coming from the same firearm when in fact it did not (i.e., the random match probability).

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.114
GPT teacher head0.330
Teacher spread0.217 · 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 designOther design
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Forensic SciencesSame topicForensic and Genetic ResearchFrench-language works237,207