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Record W4414301282 · doi:10.1002/cjce.70074

Optimization of lipolysis variables of tengkawang seed fat (illipe butter) using frangipani resin derived lipase

2025· article· en· W4414301282 on OpenAlexvenueno aff
Fikra Hanifah, Astri Nur Istyami, Meiti Pratiwi, Dwi Hantoko, Tirto Prakoso

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsnot available
Fundersnot available
KeywordsLipolysisLipaseFactorial experimentResponse surface methodologyCentral composite designFractional factorial designEnzymeStearic acid

Abstract

fetched live from OpenAlex

Abstract This study aimed to determine the optimum conditions for the lipolysis of tengkawang fat using lipase derived from frangipani resin to produce free fatty acids, which, particularly stearic acid, serve as key intermediates in various industrial applications. A 2 (4–1) fractional factorial design was used to screen the effects of pH, temperature, enzyme concentration, and buffer‐to‐fat ratio on the degree of lipolysis. The 5‐h reaction yielded a reaction mass of 43.35% of free fatty acids. ANOVA results revealed that pH, enzyme concentration, and their interaction were significant, with curvature present at the centre point. Optimization was then conducted using response surface methodology (RSM) with a face‐centred central composite design (FCCCD). The highest degree of lipolysis achieved was 89.54% under the conditions of pH 7, temperature 27°C, enzyme concentration 10%, and a buffer‐to‐fat ratio of 2:1. Time profile observations showed that the lipolysis reaction proceeded slowly, reaching 89.53% at the end of 24 h.

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)0.000
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 score0.261
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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