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Record W2586534281 · doi:10.1111/1541-4337.12255

Antimicrobials from Mushrooms for Assuring Food Safety

2017· article· en· W2586534281 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

VenueComprehensive Reviews in Food Science and Food Safety · 2017
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
FundersFujian Academy of Agricultural Sciences
KeywordsFood safetyFood scienceAntimicrobialBusinessBiotechnologyBiologyMicrobiology

Abstract

fetched live from OpenAlex

The interest in discovering and developing natural antimicrobials has significantly increased due to consumer preferences for foods that are free of chemical preservatives while still microbiologically safe. One of the best sources of natural antimicrobials is certain mushrooms (fungi) as many of them not only have nutraceutical functions but also possess antimicrobial properties. This article reviews the available information on mushroom antimicrobials for food safety control. It includes available resources, extraction procedures, antimicrobial activities, and the status of their applications to food safety. The review indicates that there are great potential benefits to be gained from mushroom antimicrobials in food production, processing, and preservation as a biosolution to meet the increasing demands for food quality and safety.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.103
GPT teacher head0.355
Teacher spread0.252 · 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