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Record W4416917498 · doi:10.51731/cjht.2025.1299

Fecal Microbiota (Rebyota)

2025· article· W4416917498 on OpenAlexaboutno aff
CDA-AMC

Bibliographic record

VenueCanadian Journal of Health Technologies · 2025
Typearticle
Language
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
Fundersnot available
KeywordsClostridioidesAntibioticsAntibiotic therapyDrugPublic healthPharmacotherapy

Abstract

fetched live from OpenAlex

Canada’s Drug Agency (CDA-AMC) recommends that Rebyota be reimbursed by public drug plans for the prevention of recurrence of Clostridioides difficile infection (CDI) in adults if certain conditions are met. Rebyota should only be covered for adult patients who have experienced 2 or more recurrences of CDI despite appropriate antibiotic treatment for previous episodes. Rebyota is administered after completing antibiotic therapy for the current CDI recurrence. Rebyota should only be reimbursed if prescribed and administered by doctors and care teams who are experienced in treating repeat CDI and in using this type of treatment, and if the cost of Rebyota is reduced. Rebyota should only be reimbursed as 1 dose. If CDI comes back after that first dose, patients may be able to get another dose for each recurrence, if the original initiation criteria are met.

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)0.003
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: none
Teacher disagreement score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.010

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 head0.028
GPT teacher head0.328
Teacher spread0.300 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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