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Record W2783591195 · doi:10.1111/1556-4029.13726

Exploitation of the Ultraviolet Properties and Machine Cut Edges of Paper to Associate and Sequence Sheets in a Ream

2018· article· en· W2783591195 on OpenAlexaff
Nicola R. Musgrave, Oliver T. S. Thorne

Bibliographic record

VenueJournal of Forensic Sciences · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsUltravioletLine (geometry)Sequence (biology)Ultraviolet lightComputer scienceProcess (computing)Engineering drawingCombinatoricsAlgorithmArtificial intelligenceMaterials scienceEngineeringChemistryMathematicsOptoelectronicsGeometry

Abstract

fetched live from OpenAlex

Previously unreported line patterns visible under ultraviolet light were observed on a proportion of plain white A4 printer/copier paper from different manufacturers. These Ultraviolet Line Patterns (UVLPs) usually appear as stripes down the vertical length of the paper. Typically, the UVLPs were found to "repeat" through the ream in a predictable way, while also changing. It is postulated that the repeating nature of the UVLPs is a result of the way that paper is manufactured. This leads to the ability to sequence the sheets compared to their original source paper. Even in the absence of UVLPs, it is possible to use our observation of the manufacturing process to anticipate the order of several sheets of paper and conclusively associate them, in some cases, by physically fitting their machine cut edges and crossing paper fibers. Such a novel approach to examining questioned documents would be highly useful in forensic casework.

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 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 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 score0.191
Threshold uncertainty score0.330

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 studies0.0000.001
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 head0.113
GPT teacher head0.265
Teacher spread0.152 · 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 teacher head, 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

Citations3
Published2018
Admission routes1
Has abstractyes

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