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Record W2953816775 · doi:10.1139/er-2018-0124

A brief review of palm oil liquid waste conversion into biofuel

2019· review· en· W2953816775 on OpenAlexvenueno aff
Muhammad Zuber, Wira Jazair Yahya, Ahmad Muhsin Ithnin, Dhani Avianto Sugeng, Hasannuddin Abd Kadir, Mohamad Azrin Ahmad

Bibliographic record

VenueEnvironmental Reviews · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBiofuelPulp and paper industryChemistryBiodieselTransesterificationPalm oilOil millBiogasVegetable oil refiningEnvironmental scienceWaste managementFood scienceBiochemistryOrganic chemistryMethanol

Abstract

fetched live from OpenAlex

Palm oil is an important edible oil because of its high content of beta-carotene and vitamin E, high oil output, and solid fat content. However, its extensive commercialization has resulted in a vast amount of waste, leading to challenges for the development of an economically feasible conversion of palm oil waste into useful products. This review focuses on exploring the various conversion processes of the liquid waste produced from the palm oil processing industry. The main treatment of palm oil mill effluent (POME), which can be separated into fiber, wastewater, residual oils, and other impurities, involves a digestion process that produces biogas, while the fiber and other impurities are often converted into animal feed, soil fertilizer, fermentation media, and yeast production. Residual oil found in POME, known as sludge palm oil (SPO), contains high levels of free fatty acid (FFA). Other residual oils resulting from palm oil refining include palm fatty acid distillate (PFAD) and palm acid oil (PAO) that also have a high FFA content. The transesterification and esterification processes are utilized to convert SPO, PFAD and PAO into fuel.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.011

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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2019
Admission routes1
Has abstractyes

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