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Record W2075169926 · doi:10.1002/cjce.21848

Quantitative analysis of fatty acids composition in the used cooking oil (UCO) by gas chromatography−mass spectrometry (GC–MS)

2013· article· en· W2075169926 on OpenAlexvenueno aff
Sumaiya Zainal Abidin, Dipesh Patel, Basudeb Saha

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsnot available
FundersUniversiti Malaysia Pahang
KeywordsChemistryGas chromatography–mass spectrometryChromatographyGas chromatographyMass spectrometryComposition (language)Fatty acid methyl esterFatty acidBiodieselOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A simple, robust and reliable method has been developed for the quantification of fatty acids in used cooking oil (UCO) by gas chromatography–mass spectrometry (GC–MS). Four steps involved in this study are: the preparation of UCO for quantification analysis, development of calibration curve, determination of fatty acids composition and the ageing studies. The developed method has been validated with known composition of the UCO and biodiesel and the error has been found to be within ±0.7%. This method can be used for the determination of composition of fatty acids and fatty acid methyl esters (FAME) in oil and biodiesel products.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.222
Teacher spread0.211 · 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 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

Citations44
Published2013
Admission routes1
Has abstractyes

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