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Record W4250630288 · doi:10.31665/jfb.2019.5187

Bioaccessibility and antioxidant activities of finger millet food phenolics

2019· article· en· W4250630288 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 Bioactives · 2019
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsMemorial University of Newfoundland
FundersNational Research Council Sri Lanka
KeywordsFood scienceChemistrySteamingRoastingAntioxidantDigestion (alchemy)Cooking methodsHigh-performance liquid chromatographyPhenolsBoilingPolyphenolFerulic acidPhenolic acidFood composition dataChromatographyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Finger millet flour was used to prepare five different foods using steaming, pressure cooking, dry roasting and open boiling as representative preparation methods. The soluble and bound phenolics of freeze dried foods were extracted. The gastric and intestinal bioaccessibility and potential absorption of phenolic compounds of foods were determined accommodating a simulated in vitro digestion model. The phenolic extracts of foods and supernatants collected at different stages of in vitro digestion were examined for their phenolic contents and antioxidant activities. The content of ferulic acid, of phenolic extracts of foods were determined using high performance liquid chromatography (HPLC). The open pan boiling retained higher content of phenolics and showed higher antioxidant activities compared to other food preparations. The release of phenolic compounds increased stepwise from gastric to intestinal phase for all foods and the bioaccessibility and potential absorption of phenolic compounds depended on the food preparation methods.

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 score0.113
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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