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The Potential Use of Mushrooms β-Glucans in the Food Industry

2014· article· en· W2041049558 on OpenAlexvenueno aff
Israilides Cleanthes, Eleftheriadis Eleftherios, Mavraganis Vassilis

Bibliographic record

VenueInternational Journal of Biotechnology for Wellness Industries · 2014
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional foodImmune systemPolysaccharideBiologyInnate immune systemFood industryHuman healthGlucanBiotechnologyFood scienceChemistryBiochemistryImmunologyMedicine

Abstract

fetched live from OpenAlex

Many edible mushrooms are considered as "functional" foods having immunomodulatory and anticancer properties. The ability of mushrooms to exert biological effects and modulate immune functions is due to the presence of bioactive compounds with most important the polysaccharides -glucans. B-glucans are found in bacteria, fungi and plants and act on several immune cell receptors resulting in both innate and adaptive response. The incorporation ofglucans in various foods and animal feed has the potential of creating novel "functional" food products, with many health benefits to human and animal nutrition.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.287
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations9
Published2014
Admission routes1
Has abstractyes

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