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Fragmentation of Lignin from Organosolv Black Liquor by White Rot Fungi

2015· article· en· W1998337421 on OpenAlexaff
Djanira Rodrigues Negrão, Mohini Sain, Alcides Lopes Leão, Javad Sameni, R. S. Jeng, João Paulo Furlan de Jesus, Regina Teresa Rosim Monteiro

Bibliographic record

VenueBioResources · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrganosolvLigninWhite rotBlack liquorPulp and paper industryFragmentation (computing)White (mutation)Materials scienceBotanyChemistryEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

The mycelial growth ability of 13 white rot fungi were separately evaluated in kraft, organosolv, and soda black liquor agar-plates. The fungus able to best grow and decolorize black liquor agar-plates was grown in organosolv black liquor to investigate whether it reduced organosolv lignin molar mass. The fungus Bjerkandera adusta showed fair mycelial growth and decolorization ability in 10% black liquor-agar plates. To obtain low-molecular weight (MW) lignin, B. adusta was cultivated in 150-mL Erlenmeyer flasks containing 10% black liquor and maintained in a shaking culture for 15 days. Lignin was recovered from each Erlenmeyer flask by acid precipitation and was analysed by size exclusion chromatography (SEC) and Fourier transform infrared (FTIR) spectroscopy. The lowest MW of lignin from black liquor was observed on the 11th and 12th days, at 1461 and 1790 kDa, respectively, with the polydispersity close to 1.0, indicating that the molecules were similar in size. Fourier transform infrared spectra bands showed modification of the lignin structure during 9 days, with new bands appearing after five days of lignin biodegradation.

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 score0.117
Threshold uncertainty score0.246

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 head0.019
GPT teacher head0.201
Teacher spread0.182 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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