MétaCan
Menu
Back to cohort
Record W2358037407

Research on the Utilization of Cellulase in Liquor Distiller's Grains

2009· article· en· W2358037407 on OpenAlexaff
Qiang Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsCellulaseFlavorPulp and paper industrySugarFood scienceFermentationDistilled waterEnvironmental scienceChemistryCelluloseEngineeringChromatographyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

The resource utilization of Maotai-flavor liquor by cellulase was studied.The results showed that the addition of 10 U/g cellulase in the residual distiller's grains could effectively increase the content of reducing sugar after 5 h water bathing in water bathing pot at 58 ℃,the alco-holicity by the fermentation of the residual distiller's grains could reach 4.67 %vol,and liquor yield could reach 31.39 %(increasing by 2.61 % than untreated distiller's grains).The distilled liquor product could meet the requirements of quality Maotai-flavor liquor and its sanitary indexes were in accord with the related standards.The addition of cellulase could enhance the use value of Maotai-flavor distiller's grains.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.312
GPT teacher head0.380
Teacher spread0.068 · 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 designObservational
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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicFood Quality and Safety StudiesFrench-language works237,207