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Record W2161124070 · doi:10.1080/10575630108041280

Microwave-assisted Extraction of Phenolic Compounds from Grape Seed

2001· article· en· W2161124070 on OpenAlex
Ni Hong, Varoujan A. Yaylayan, G. S. V. Raghavan, J. R. Jocelyn Paré, Jacqueline M.R. Bélanger

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

VenueNatural product letters · 2001
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsMcGill UniversityEnvironment and Climate Change CanadaSte. Anne's Hospital
Fundersnot available
KeywordsPolyphenolExtraction (chemistry)ChemistryTannic acidYield (engineering)ChromatographyReagentSolventBotanyOrganic chemistryAntioxidantBiologyMaterials science

Abstract

fetched live from OpenAlex

A microwave-assisted extraction technique was developed to optimize the extraction of phenolic compounds from grape seeds. The microwave power (300-150W) and time of extraction (20-200s) were varied during the optimization process. The polyphenol content of the resulting extracts were measured as mg of tannic acid equivalent per gram of crude extract (mg TAE/g of crude extract), using a Folin-Ciocalteau reagent. In general, neither the time nor the power had a significant effect on the overall % yield (average of 13.5%) and on the polyphenol content (392 mg TAE/g of crude extract) of the extracts. However, when the solvent polarity was changed by the addition of 10% water, the yield increased to 15.2% and the polyphenol content increased to 429 mg TAE/g of crude extract.

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)0.000
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 score0.224
Threshold uncertainty score0.521

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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