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Dilute Sulfuric Acid Hydrolysis of Pennisetum (sp.) Hemicellulose

2017· article· en· W2595231848 on OpenAlexaff
Zhongjian Tian, Jiachuan Chen, Xingxiang Ji, Qiang Wang, Guihua Yang, Pedram Fatehi

Bibliographic record

VenueBioResources · 2017
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsLakehead University
Fundersnot available
KeywordsHemicelluloseXyloseSulfuric acidHydrolysisHydrolysateChemistryPennisetumAcid hydrolysisFourier transform infrared spectroscopyXylanYield (engineering)Extraction (chemistry)Nuclear chemistryMaterials scienceChromatographyOrganic chemistryChemical engineeringBotanyFermentation

Abstract

fetched live from OpenAlex

Dilute sulfuric acid hydrolysis of Pennisetum (sp.) hemicellulose was investigated in this work. The hemicellulose was obtained by ethanol precipitation of hydrolysate produced via the microwave-assisted H2O2-NaOH extraction from the Pennisetum (sp.). Acid hydrolysis was performed by varying the process parameters, including the sulfuric acid concentration, hydrolysis temperature, solid to liquor ratio, and the reaction time. The xylose yield was selected as the target of process optimization and the orthogonal experiment of L9 (34) was designed to optimize the process conditions. The highest xylose yield of 86.5% could be obtained under the conditions of an acid concentration of 1%, the hydrolysis temperature of 105 °C, a solid to liquor ratio of 1:15, and a reaction time of 4 h. Fourier transform infrared spectroscopy (FTIR) analysis confirmed that most of the hemicellulose had been depolymerized into xylose.

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 score0.001
Threshold uncertainty score0.002

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 head0.011
GPT teacher head0.204
Teacher spread0.194 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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