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The Effect of Electrostatic Fingerprint Visualization on Integrated Ballistic Identification Systems

2011· article· en· W2112118191 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Forensic Sciences · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicForensic Fingerprint Detection Methods
Canadian institutionsCentre de Santé et de Services Sociaux Cavendish
Fundersnot available
KeywordsFingerprint (computing)Identification (biology)VisualizationComputer scienceEngineeringArtificial intelligenceBiology

Abstract

fetched live from OpenAlex

Visualization of fingerprint corrosion on spent brass cartridge cases by the application of a high electrical potential and conducting carbon powder is becoming an accepted method of fingerprint enhancement. However, to date, no examination has been made of any effect this technique has on ballistic identification. To resolve this, images of the breech face and firing pin marks were captured on six plated nickel and six brass primer cup spent cartridge cases. Three nickel and three brass cases were then subjected to the application of a potential of +2500 V for a period of 1 min. The remaining cases were additionally subjected to the application of carbon powder. These latter cases were then washed to remove all traces of powder. Each case was recaptured with the same ballistic identification apparatus and imaging procedure. None of the twelve cases showed any visual difference after the application of the potential or conducting powder.

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.

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)0.011
metaresearch head score (Gemma)0.005
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 score0.735
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
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 head0.040
GPT teacher head0.359
Teacher spread0.319 · 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