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Record W3097939593 · doi:10.1093/chromsci/bmaa082

Untargeted SPME–GC–MS Characterization of VOCs Released from Spray Paint

2020· article· en· W3097939593 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 Chromatographic Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicForensic Fingerprint Detection Methods
Canadian institutionsOntario Tech UniversityTrent University
Fundersnot available
KeywordsChemistrySolid-phase microextractionChromatographyGas chromatography–mass spectrometryContext (archaeology)Environmental chemistryVolatile organic compoundMass spectrometryHydrocarbonGas chromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Paints are a common form of physical evidence encountered at crime scenes. This research presents an optimized method for the untargeted analysis of volatile organic compounds (VOCs) in spray paint using solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). The presence and persistence of VOCs were monitored in 30 minute intervals, over a 4 hour period, in a triplicate time study. As predicted, spray paint solvents are lost to the environment readily, whereas few VOCs remained present in the headspace in low concentrations beyond 4 hours. The VOCs that were observed to have the highest persistence in the headspace were aromatic compounds and those with longer hydrocarbon chains. We present this study in a forensic science context and suggest that the interpretation of the results may be useful for forensic applications in establishing a time since deposition of a spray-painted surface.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.504
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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