MétaCan
Menu
Back to cohort

Optimization of Extraction of Anthocyanins from Black Currants with Aqueous Ethanol

2003· article· en· W2067077601 on OpenAlex

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 Food Science · 2003
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsChemistrySolventExtraction (chemistry)Yield (engineering)EthanolAntioxidantAqueous solutionChromatographyComposition (language)Food scienceBiochemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

ABSTRACT: Extraction of anthocyanins from black currants using aqueous ethanol was optimized for yield and antioxidant activity. The process variable having the most effect on the extraction was the solvent to solid ratio, which increased phenolic extraction in the whole range from 0 to 19 L/kg. Total phenolics increased with ethanol concentration up to a maximum at about 60% and then decreased with further increase in solvent concentration irrespective of the solvent to solid ratio. Temperature only affected the extraction of anthocyanins. Increasing the temperature beyond 30 to 35 °C resulted in degradation of anthocyanins and reduction of yields. Variation in extract composition was not sufficiently large to affect antioxidant activity.

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 score0.003
Threshold uncertainty score0.163

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 head0.022
GPT teacher head0.285
Teacher spread0.264 · 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