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Record W1561967882 · doi:10.15376/biores.2.4.682-692

Bio-modification of eucalyptus chemithermo-mechanical pulp with different white-rot fungi

2007· article· en· W1561967882 on OpenAlexafffund
Yang Qi-feng, Shuangfei Wang, Shiyu Fu, Kecheng Li

Bibliographic record

VenueBioResources · 2007
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of New Brunswick
FundersNew Brunswick Innovation Foundation
KeywordsPhanerochaeteChrysosporiumPulp (tooth)LigninCelluloseWhite rotEucalyptusUltimate tensile strengthChemistryPulp and paper industryFood scienceMaterials scienceHorticultureBotanyComposite materialBiologyOrganic chemistryMedicine

Abstract

fetched live from OpenAlex

Modification of chemithermomechanical pulp (CTMP) by fungal treatment was investigated. Eucalyptus CTMP was treated with three different types of white-rot fungi, namely, Phanerochaete chrysosporium (P.c-1767), Trametes hirsute 19-6 (T.h-19-6), and Trametes hirsute19-6w (T.h-19-6w), under a stationary culture condition. Pulp total weight loss, lignin loss, and cellulose loss were determined to compare the different enzymes secreted by the three fungal strains. Pulp physical strengths, optical properties, and bleachability after the fungal treatment were investigated to compare the effect of fungal treatment on the pulp quality improvement. The results show that lignin reduction by both T.h-19-6 and T.h-19-6 (w) was about twice as much as that by P.c-1767. However, the selectivity of T.h-19-6 (w) towards lignin over cellulose was only 0.82, while that of T.h-19-6 was as high as 4.43. After T.h-19-6 treatment, pulp tensile, tear, and internal bonding strength increased by about 27%, 38%, and 40%, respectively.

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 score0.007
Threshold uncertainty score0.488

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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

Citations11
Published2007
Admission routes2
Has abstractyes

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