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Record W2086542186 · doi:10.1021/ie040288r

Continuous Dyeing of Cotton with Reactive Dyes Using Infrared Heat

2005· article· en· W2086542186 on OpenAlexaff
Arthur D. Broadbent, Julienne Bissou-Billong, Miriem Lhachimi, Y. Mir, Serge Capistran

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicDyeing and Modifying Textile Fibers
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDyeingMaterials scienceReactive dyeElectrolytePulp and paper industryChemical engineeringChemistryComposite materialElectrode

Abstract

fetched live from OpenAlex

Fabrics containing cotton fibers were dyed in a continuous process by impregnating the fabric with an alkaline solution of reactive dyes and then drying and heating it using electrically generated infrared radiation followed by hot air. Optimal fixation of the dyes required a strongly alkaline dye solution and heating the fabric to as high a temperature as possible consistent with avoiding thermal damage to the fibers. Color consistency and quality were well-controlled along the fabric length during both pilot- and industrial-scale continuous dyeing and the color differences, relative to commercial products obtained by batch dyeing procedures with the same recipes, were small. The infrared process offers reduced pollution loads in the washing liquors from reactive dyeing because fixation yields were greater than those for the cold pad-batch dyeing procedure, and no electrolytes or urea were needed in the initial dye solutions.

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 head0.073
GPT teacher head0.300
Teacher spread0.227 · 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

Citations7
Published2005
Admission routes1
Has abstractyes

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