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Record W1518864832 · doi:10.5539/mas.v9n7p206

Production of Xylitol from Oil Palm Empty Friuts Bunch: A Case Study on Bioefinery Concept

2015· article· en· W1518864832 on OpenAlexvenueno aff
Efri Mardawati, Tjandra Setiadi

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
FundersDirektorat Jenderal Pendidikan Tinggi
KeywordsXylitolHemicellulosePulp and paper industryBiorefineryXyloseLigninBiomass (ecology)CelluloseHydrolysateSugarPalm oilBiofuelWaste managementHydrolysisChemistryFood scienceEnvironmental scienceFermentationOrganic chemistryAgronomyEngineering

Abstract

fetched live from OpenAlex

The concept of biorefinery offers the utilization of biomass, in particular agricultural waste, to be converted intoenergy, chemicals, materials, and food. In 2013 Indonesia produced about 27.4 thousand tons of crude palm oil(CPO) which corresponds to approximately 30 thousand tons of oil palm empty fruit bunches (EFB), the biomasswaste from palm oil industries. The huge availability of EFB in Indonesia may serve as a good starting point toimplement the concept of biorefinery. EFB mainly comprises of cellulose, hemicellulose and lignin. Thecellulosic components of EFB have been thoroughly studied, i.e. for the production of bioethanol. Thehemicellulosic component of EFB, which is a polymeric substance that comprises mainly of xylose, has beenbarely explored. This paper reviewed the potential utilization of hemicellulosic component of EFB to beconverted to xylitol, the 5-carbon-sugar-alcohol which is low calorie, low Glycemic Index, and anti-cariogenic.The pretreatment and hydrolysis of EFB and the following fermentation of EFB hydrolysate to xylitol will bediscussed further.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.250
Teacher spread0.206 · 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

Citations34
Published2015
Admission routes1
Has abstractyes

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