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Record W2736345078 · doi:10.3920/bm2016.0222

How do probiotics and prebiotics function at distant sites?

2017· review· en· W2736345078 on OpenAlexaff
Gregor Reid, Thomas Abrahamsson, Michael T. Bailey, Laure B. Bindels, Rostyslav Bubnov, Kriston Ganguli, Christopher Martoni, Catherine O’Neill, Hélène M. Savignac, Catherine Stanton, Noam Ship, Michael G. Surette, Kieran Tuohy, Saskia van Hemert

Bibliographic record

VenueBeneficial Microbes · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsBioPhage Pharma (Canada)Lawson Health Research InstituteWestern University
Fundersnot available
KeywordsSynbioticsMicrobiomeGut microbiomeGut floraBiologyMedicineBioinformaticsProbioticImmunology

Abstract

fetched live from OpenAlex

The realisation that microbes regarded as beneficial to the host can impart effects at sites distant from their habitat, has raised many possibilities for treatment of diseases. The objective of a workshop hosted in Turku, Finland, by the International Scientific Association for Probiotics and Prebiotics, was to assess the evidence for these effects and the extent to which early life microbiome programming influences how the gut microbiota communicates with distant sites. In addition, we examined how probiotics and prebiotics might affect the skin, airways, heart, brain and metabolism. The growing levels of scientific and clinical evidence showing how microbes influence the physiology of many body sites, leads us to call for more funding to advance a potentially exciting avenue for novel therapies for many chronic diseases.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.059
GPT teacher head0.325
Teacher spread0.266 · 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

Citations82
Published2017
Admission routes1
Has abstractyes

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