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Record W2070293203 · doi:10.1111/1556-4029.12620

The Effect of <scp>pH</scp> on Electrolyte Detection of Fingermarks on Cartridge Cases and Subsequent Microscopic Examination

2014· article· en· W2070293203 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Forensic Sciences · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicForensic Fingerprint Detection Methods
Canadian institutionsAmorfix (Canada)
FundersUniversity of Toronto Mississauga
KeywordsCartridgeElectrolyteMaterials scienceChromatographySodium hydroxideChemistryMetallurgyOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

Cartridge cases may contain deposited fingermarks when the firearm was loaded (http://www.nij.gov/pubs-sum/225320.htm, J Forensic Sci, 53, 2008 and 812). Cartridge cases can be individualized with microscopic examination. However, heat and friction degrades the deposited fingermark on the fired cartridge cases, if any on the surface. Also, unfired and fired cartridge cases are made of metal, which is a nonporous surface that does not retain fingermarks well (http://www.nij.gov/pubs-sum/225320.htm). This study tests the effects of pH level on fingermark clarity on brass fired and unfired cartridge cases and microscopic striation examination (MSE). Two trials were performed to determine the optimal pH in fingermark clarity for both types of cartridges. This was performed through immersion in six pH range solutions from dilutions of sulfuric acid and sodium hydroxide for 24 h for the purpose of enhancing the fingermarks on the metal. The use of the optimal neutral pH level is suggested because immersion of the cartridge cases in pH 1-3 and 3-5 affects MSE.

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)0.010
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.713
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.312
Teacher spread0.296 · 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