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Record W3174489285 · doi:10.31018/jans.v13i2.2683

Probiotics as a boon in Food diligence: Emphasizing the therapeutic roles of Probiotic beverages on consumers' health

2021· article· en· W3174489285 on OpenAlexaff
Feroze Mohamed Khan, Sonia Morya, Vijay Kumar Chattu

Bibliographic record

VenueJournal of Applied and Natural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Toronto
FundersLovely Professional University
KeywordsProbioticHealth benefitsBusinessBifidobacteriumBiotechnologyHuman healthFood scienceLactobacillusMedicineBiologyEnvironmental healthTraditional medicine

Abstract

fetched live from OpenAlex

Probiotics are living microorganisms that improve health when eaten or introduced to the body. They have become an essential aspect of everyone’s life now due to these products growing health benefits. They contain live bacteria that help our gut maintain good gut microflora and keep us healthy. Lactobacillus and Bifidobacterium are the most used probiotic strains. Everyone knows the importance of these products nowadays and has highlighted the parts that a reader must know about these products and how they affect the human body. This review discusses probiotics, dairy-based probiotics, non-dairy based probiotics and their role in therapeutics. This review has also been elaborated on an essential by-product of the dairy industry, i.e., whey, which has many health benefits and highly recommended for people who are in sports and body-building. While analysing the health benefits of probiotic supplements, there is a lot to discuss,i.e. how and where probiotic products work in our body and provide us with different health benefits. The most common way a probiotic performs is by boosting our immune system and fighting diseases. While looking at the market part of probiotic products globally, it is a multibillion-dollar market mostly based in Europe, where people are more health-conscious. The probiotic market has now frowned worldwide and is one of the most profitable markets in the current world.

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)0.000
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 score0.297
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.248
Teacher spread0.236 · 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 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

Citations12
Published2021
Admission routes1
Has abstractyes

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