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Record W1593357338 · doi:10.3402/mehd.v26.27799

Changes in vaginal microbiota following antimicrobial and probiotic therapy

2015· article· en· W1593357338 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

VenueMicrobial Ecology in Health and Disease · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsBacterial vaginosisLactobacillus rhamnosusLactobacillus crispatusGardnerella vaginalisProbioticMicrobiologyAntimicrobialLactobacillus reuteriLactobacillusBifidobacterium bifidumPrevotellaBiologyMedicineBacteriaLactobacillus acidophilus

Abstract

fetched live from OpenAlex

BACKGROUND: The composition of the vaginal microbiota is known to be important for health. When infections occur, antimicrobial therapy is often poorly efficacious. OBJECTIVE AND DESIGN: We used 16S rRNA gene sequencing to characterize changes in the bacterial microbiota following oral antimicrobial and probiotic interventions. RESULTS: While the bacterial vaginal profiles of women with vulvovaginal candidiasis were dominated by lactobacilli as in healthy women, and unchanged by therapy, Gardnerella vaginalis, Prevotella, Atopobium, Sneathia, and Megasphaera dominated the vagina of women with bacterial vaginosis (BV), and treatment with tinidazole plus Lactobacillus reuteri RC-14+L. rhamnosus GR-1 resulted in an increased relative abundance of indigenous L. iners or L. crispatus. CONCLUSIONS: The ability to restore homeostasis provides a rationale for conjoint use of probiotics with antibiotic treatment of BV.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.316
Teacher spread0.283 · 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