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Coloration of Polyester Fibers for Securities Protection from Counterfeit

2015· article· en· W2035471347 on OpenAlexvenueno aff
V. A. Goldade, N.V. Kuzmenkova, V. E. Sytsko

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials sciencePolyesterLuminescenceComposite materialFiberCrazingPolymerOptoelectronics

Abstract

fetched live from OpenAlex

The results of modifying polyester fibers with luminescent colorants by crazing mechanism have been given. By means of REM and AFM stages of crazes initiation, their transformation into fibrillar structure of fiber and redistribution of modifiers incorporated into crazes in the surface layer of fiber have been revealed. Techniques of concentrating luminescent colorants on local sections of fiber with alternation of unprocessed segments and segments containing target additives have been described. Polyester fibers with alternating by length sections of luminescent division of colors have been obtained. It was shown that effective fiber coloration takes place when the drawing out degree ε* is between 2 and 3. Fibers modified by Oxazine and Rhodamine colorants are characterized by highest intensity of luminescence in UV radiation. The conclusion has been made that technology of modifying chemical fibers by cazing mechanism allowing implementing measured incorporation of target additives on local sections of fiber satisfy in the optimal way the protection criteria of paper filled with such fibers from counterfeiting.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.120
GPT teacher head0.389
Teacher spread0.269 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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