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Record W1974612590 · doi:10.1021/jf026068a

Optimization of Microwave-Assisted Extraction (MAP) for Ginseng Components by Response Surface Methodology

2003· article· en· W1974612590 on OpenAlex
Joong‐Ho Kwon, Jacqueline M.R. Bélanger, J. R. Jocelyn Paré

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2003
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsSaponinResponse surface methodologyGinsengCentral composite designExtraction (chemistry)Yield (engineering)GinsenosideChromatographyChemistryEthanolMicrowaveMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Response surface methodology (RSM) was applied to predict optimum conditions for microwave-assisted extraction-a MAP technology-of saponin components from ginseng roots. A central composite design was used to monitor the effect of ethanol concentration (30-90%, X(1)) and extraction time (30-270 s, X(2)) on dependent variables, such as total extract yield (Y(1)), crude saponin content (Y(2)), and saponin ratio (Y(3)), under atmospheric pressure conditions when focused microwaves were applied at an emission frequency of 2450 MHz. In MAP under pre-established conditions, correlation coefficients (R (2)) of the models for total extract yield and crude saponin were 0.9841 (p < 0.001) and 0.9704 (p < 0.01). Optimum extraction conditions were predicted for each variable as 52.6% ethanol and 224.7 s in extract yield and as 77.3% ethanol and 295.1 s in crude saponins, respectively. Estimated maximum values at predicted optimum conditions were in good agreement with experimental values.

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.

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 score0.067
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.265
Teacher spread0.233 · 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