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Record W1993181145 · doi:10.1002/cjce.21798

Xylanase and laccase aided bio‐bleaching of wheat straw pulp

2013· article· en· W1993181145 on OpenAlexvenueno aff
Bhavin S. Dedhia, Mangesh D. Vetal, Virendra K. Rathod, Levente Csóka

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsnot available
Fundersnot available
KeywordsXylanaseLaccaseKappa numberPulp (tooth)ChemistryStrawPulp and paper industryChlorine dioxideChlorineFood scienceEnzymeBiochemistryOrganic chemistryDentistryKraft process

Abstract

fetched live from OpenAlex

Abstract This paper illustrates the application of enzymes (e.g. xylanase and laccase) in the bio‐bleaching of non‐woody material (e.g. wheat straw). The objective of this paper is to develop an alternative bleaching sequence avoiding the use of chlorine during bleaching. In the study, wheat straw pulp has been treated with commercially available xylanase and laccase separately and sequentially. Optimised parameters for the xylanase pre‐treatment are pH 5.5, temperature 60°C, enzyme dose 6 IU/g, pre‐treatment time 75 min and speed of agitation 80 rpm. Similarly, optimum parameters for laccase delignification are pH 3.5, temperature 60°C, enzyme dose 22.5 IU/g of oven dried pulp, mediator concentration 1.5% of oven dried pulp (odp), delignification time 10 h and speed of agitation 120 rpm. On the other hand, sequential treatments such as xylanase pre‐treatment (X) followed by laccase (L) and alkaline perdoxide (E) in presence of mediator have shown better reduction in kappa number, that is 24.84% as compared to LE in presence and absence of a mediator.

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)0.000
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 score0.023
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.163
Teacher spread0.154 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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