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Record W2213542931 · doi:10.1155/2015/628630

Should Pediatric Infectious Diseases Physicians be Proponents of Probiotics?

2015· article· en· W2213542931 on OpenAlexaff
Joan Robinson

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of AlbertaStollery Children's Hospital
Fundersnot available
KeywordsProbioticMicrobiologyAntimicrobialImmune systemBacteriaBiologyFlora (microbiology)Gastrointestinal tractImmunityPathogenBacteriocinColonizationPathogenic bacteriaImmunology

Abstract

fetched live from OpenAlex

Probiotics are live bacteria or fungi deliberately introduced into the gastrointestinal (GI) tract in an attempt to prevent or treat a disease state. Probiotics are believed to work using three mechanisms (1,2). The first is a direct antimicrobial effect. Probiotic strains are postulated to ‘crowd out’ pathogenic GI flora and to compete with them for elements, such as iron, to act as ‘decoy binding sites’, such that pathogens bind to them rather than to mucosal surfaces and to produce antibacterial products including bacteriocins (bacterial toxins that inhibit other bacteria), hydrogen peroxide and organic acids. The second mechanism is alteration of the GI mucosal barrier. Colonization of probiotic strains may prevent pathogens from damaging the mucosa and invading. The third mechanism is through effects on mucosal immunity, leading to nonspecific humoral immune responses, production of protective cytokines and induction of regulatory T cells, which have an anti-inflammatory effect. Despite decades of use, the efficacy of probiotics for many indications remains unclear. Reasons for this include:

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)0.003
metaresearch head score (Gemma)0.019
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0190.005

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 head0.015
GPT teacher head0.223
Teacher spread0.208 · 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
GenreCommentary

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Infectious Diseases and Medical Microbiology→Same topicProbiotics and Fermented Foods→French-language works237,207→