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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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 score0.319
Threshold uncertainty score0.472

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 head0.076
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