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Record W2154793074 · doi:10.5539/mas.v9n11p68

Optimization of Eugenol Extraction from Clove Oil using Response Surface Methodology

2015· article· en· W2154793074 on OpenAlexvenueno aff
Widayat Widayat, Hadiyanto Hadiyanto, Bambang Yudi Cahyono, Ngadiwiyana Ngadiwiyana

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
FundersDirektorat Jenderal Pendidikan Tinggi
KeywordsEugenolResponse surface methodologyYield (engineering)Central composite designExtraction (chemistry)ChemistryPulp and paper industryChromatographyMaterials scienceComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The objective of this research was to obtain optimum condition of eugenol production from clove oil using a central composite design method. The main process occured in the eugenol production was saphonification and neutralization processes. In order to optimize these processes, the ratio of NaOH/clove oil and temperature were studied as design variables i.e. ratio of NaOH/clove oil=1:2.5-1:3.5 while temperature was varied between 40 and 60oC. The yield of eugenol was considered as the main response in of this experiment. The result showed that the optimum condition was achieved when the temperature and the ratio of NaOH/clove oil were 50oC and 2.75:1, respectively and the yield was 39.17%.<br />

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 score0.075
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.131
GPT teacher head0.308
Teacher spread0.177 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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