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Record W2073205821 · doi:10.1007/978-1-4612-0119-9_5

SO2-Catalyzed Steam Explosion of Corn Fiber for Ethanol Production

2002· article· en· W2073205821 on OpenAlexaff
Renata Bura, Shawn D. Mansfield, John N. Saddler, Rodney J. Bothast

Bibliographic record

VenueHumana Press eBooks · 2002
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSteam explosionBioconversionRaw materialPulp and paper industryEthanol fuelChemistryFermentationEnzymatic hydrolysisFiberHydrolysisHydrolysateEthanolWaste managementSugarRenewable resourceFood scienceBiochemistryRenewable energyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Corn fiber, a by-product of the corn wet-milling industry, represents a renewable resource that is readily available in significant quantities and could potentially serve as a low-cost feedstock for the production of fuel-grade alcohol. In this study, we used a batch reactor to steam explode corn fiber at various degrees of severity to evaluate the potential of using this feedstock in the bioconversion process. The results indicated that maximum sugar yields (soluble and following enzymatic hydrolysis) were recovered from corn fiber that was pretreated at 190 degrees C for 5 min with 6% SO2. Sequential SO2-catalyzed steam explosion and enzymatic hydrolysis resulted in very high conversion (81%) of all polysaccharides in the corn fiber to monomeric sugars. Subsequently, Saccharomyces cerevisiae was able to convert the resultant corn fiber hydrolysates to ethanol very efficiently, yielding 90-96% of theoretical conversion during the fermentation process.

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 score0.002
Threshold uncertainty score0.004

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)0.0000.000

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 head0.076
GPT teacher head0.236
Teacher spread0.159 · 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

Citations74
Published2002
Admission routes1
Has abstractyes

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