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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 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

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.059
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