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Record W2515951989 · doi:10.5539/jfr.v5n5p11

Ultraviolet-C Light Effect on the Physicochemical and Antioxidant Properties of Blackberry, Blueberry, and Raspberry Nectars

2016· article· en· W2515951989 on OpenAlexvenueno aff
José Fernando Haro-Maza, José Ángel Guerrero-Beltrán

Bibliographic record

VenueJournal of Food Research · 2016
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y TecnologíaUniversidad de las Américas Puebla
KeywordsChemistryFood scienceBlowing a raspberryAntioxidantMesophileAntioxidant capacityAscorbic acidBacteriaBiochemistryBiology

Abstract

fetched live from OpenAlex

The effect of UV-C light on foodborne microorganisms (mesophilic aerobic bacteria (MAB), molds, and yeasts), physicochemical characteristics (color, total soluble solids, pH, and acidity), and antioxidant properties (ascorbic acid, antioxidant capacity (AC), total monomeric anthocyanins (TMA), and total phenolic compounds (TPC)) in blackberry, blueberry, and raspberry nectars was evaluated. Nectars were UV-C light treated at five times (5, 10, 15, 20, and 25 minutes) at constant flow rate (16.48 mL/s). The best UV-C light treatment for the three nectars, from the microbiological point of view, was 25 min. A statistical difference (p < 0.05) in TPC, within treatment times, was observed in nectars; their content was reduced as the treatment time increased, except for the blackberry nectar. The same effect was observed for the antioxidant capacity. The TMA content increased with the UV-C light treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.048
GPT teacher head0.311
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2016
Admission routes1
Has abstractyes

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