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Probiotics and Prebiotics as Functional Ingredients in Inflammatory Bowel Disease

2008· article· en· W2036092872 on OpenAlexaff
Mirjam A.C. Looijer–Van Langen, Vimal H. Prajapati, Levinus A. Dieleman

Bibliographic record

VenueNutrition Today · 2008
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsUniversity of AlbertaCanadian Institutes of Health Research
Fundersnot available
KeywordsInflammatory bowel diseaseMedicineNutraceuticalDiseaseGut floraAntibioticsImmune systemInflammatory Bowel DiseasesIntensive care medicineImmunologyInternal medicineBiologyMicrobiology

Abstract

fetched live from OpenAlex

In Brief Probiotics and prebiotics are promising nutraceuticals that may exert a beneficial effect in many medical conditions including inflammatory bowel disease. With the increasing occurrence of antibiotic resistance, the search for medication with little side effects, and the need for options for patients with inflammatory bowel disease who are unresponsive to current therapies, research into alternative therapeutic options is justified. Preclinical studies have provided insights into the effects of probiotics and prebiotics on the immune system and gut microbiota. This new information, along with the older evidence, shows that probiotics and prebiotics may ameliorate chronic intestinal inflammation. This article gives a short overview on current knowledge of probiotics and prebiotics. Do probiotics and prebiotics have a role in disease 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.228
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2008
Admission routes1
Has abstractyes

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