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An Assessment of the Evidential Value of Automotive Paint Comparisons

2004· article· en· W2100871707 on OpenAlex
G. Edmondstone, Johan Hellman, K. Legate, G.L. Vardy, Elspeth Lindsay

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsAutomotive industryArtHumanitiesEngineering

Abstract

fetched live from OpenAlex

ABSTRACTOne of the more challenging aspects of forensic paint comparison is the assessment of the significance of the findings. This study was undertaken to assess the distinctiveness of automotive paints in order to determine their evidential value. A set of 260 automobile paint samples was collected at an auction yard from recently damaged vehicles. The samples were compared to each other using visual observation and, when required, optical microscopy and infrared spectroscopy. Two hundred sixty samples, when compared one with another, represent 33,670 sample pair comparisons. Only two sample pairs could not be distinguished when only the colour and chemical composition of the topcoat were examined. Following a detailed analysis of the full layer sequence, one indistinguishable pair remained; these came from vehicles manufactured at the same assembly plant in the same year. The results of this study provide the forensic paint examiner with information that can be used to assess the evidential value of automotive paint.RÉSUMÉUn des grands défis dans la comparaison d'échantillons de peintures en sciences judiciaires est la détermination de la signification des résultats. Cette étude a été entreprise afin d'évaluer les caractères particuliers des échantillons de peintures d'automobile en vue de déterminer leurs valeurs judiciaires. Un groupe de 260 échantillons de peinture d'automobile fut recueilli parmi des autos endommagés prévus à la vente aux enchères. Les échantillons furent comparés visuellement, par microscopie optique et par spectroscopie à l'infra-rouge. Deux cent soixante échantillons comparés l'un à l'autre représente 33,670 paires de comparaisons. Seulement deux paires d'échantillons ne pouvait pas être distingués lorsque seulement la couleur et la composition chimique de la couche supérieure furent examinées. Seulement une paire d'échantillons ne pouvaient être distinguée après une analyse détaillée de toutes les couches de peintures. Ces échantillons provenaient de véhicules fabriqués à la même manufacture d'assemblage dans la même année. Les résultats de cette étude va fournir aux examinateurs de peintures dans le domaine des sciences judicaires de l'information qui peut être utilisée pour estimer la valeur judiciaire de leurs résultats.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
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 head0.035
GPT teacher head0.298
Teacher spread0.263 · 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