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Record W2414171679 · doi:10.1520/jfs2002280

Characterization and Aging Study of Currency Ink and Currency Canine Training Aids Using Headspace SPME/GC-MS

2003· article· en· W2414171679 on OpenAlexaboutno aff
D. T. Vu

Bibliographic record

VenueJournal of Forensic Sciences · 2003
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryChromatographyAlkylOrganic chemistrySolvent

Abstract

fetched live from OpenAlex

Solid-phase microextraction/gas chromatography-mass spectrometry (SPME/GC-MS) was used to characterize the volatile components associated with U.S. currency, U.S. currency inks, and Canadian currency. Compounds that can be attributed to the ink-curing process include series of straight-chain aldehydes, alkenals, acids, alcohols, and ketones and a series of lactones and 2-alkyl furans. Solvent compounds include naphthenic and paraffinic hydrocarbons with a profile typical of petroleum products, alkyl cyclohexanes, various ethylene glycol alkyl ethers, and traces of chlorinated solvents. Trace levels of 2-phenoxyethanol, a solvent often used in ink formulations, were also detected. Environmental contaminants, those compounds found in circulating currency but not in currency ink, include 2,2'-diethyl-1,1'-biphenyl, methyl benzoate and salicylate, menthol, limonene, dimethyl and diethyl phthalate, and ionol. Not including simple hydrocarbons, over 100 compounds were identified in the headspace of currency-related samples.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.149
GPT teacher head0.435
Teacher spread0.287 · 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

Citations13
Published2003
Admission routes1
Has abstractyes

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