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Record W4256351305 · doi:10.1007/978-1-4612-0119-9_52

Cellulase Adsorption and an Evaluation of Enzyme Recycle During Hydrolysis of Steam-Exploded Softwood Residues

2002· book-chapter· en· W4256351305 on OpenAlexaff
Yanpin Lu, Bin Yang, David J. Gregg, John N. Saddler, Shawn D. Mansfield

Bibliographic record

VenueHumana Press eBooks · 2002
Typebook-chapter
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSoftwoodChemistryHydrolysisCellulaseEnzymatic hydrolysisBioconversionCelluloseAdsorptionSubstrate (aquarium)ChromatographyYield (engineering)Pulp and paper industryHardwoodWaste managementOrganic chemistryFermentationMaterials scienceBotanyComposite material

Abstract

fetched live from OpenAlex

The sugar yield and enzyme adsorption profile obtained during the hydrolysis of SO2-catalyzed steam-exploded Douglas-fir and posttreated steam-exploded Douglas-fir substrates were determined. After hot alkali peroxide posttreatment, the rates and yield of hydrolysis attained from the posttreated Douglas-fir were significantly higher, even at lower enzyme loadings, than those obtained with the corresponding steam-exploded Douglas-fir. The enzymatic adsorption profiles observed during hydrolysis of the two substrates were significantly different. Ultrafiltration was employed to recover enzyme in solution (supernatant) and reused in subsequent hydrolysis reactions with added, fresh substrate. These recycle findings suggested that the enzyme remained relatively active for three rounds of recycle. It is likely that enzyme recovery and reuse during the hydrolysis of posttreated softwood substrates could lead to reductions in the need for the addition of fresh enzyme during softwood-based bioconversion processes.

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 categoriesMeta-epidemiology (narrow)
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 score0.374
Threshold uncertainty score1.000

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 head0.066
GPT teacher head0.240
Teacher spread0.174 · 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.

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

Citations33
Published2002
Admission routes1
Has abstractyes

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