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Cochrane Rapid Reviews Methods Group offers evidence-informed guidance to conduct rapid reviews

2020· article· en· W3092985072 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Clinical Epidemiology · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityCochraneOttawa HospitalCanadian Agency for Drugs and Technologies in HealthUniversity of Ottawa
FundersDonau-Universität KremsOttawa Hospital Research Institute
KeywordsSystematic reviewInterimMedicineCochrane collaborationMEDLINEEvidence-based medicineFamily medicineAlternative medicineMedical educationPathologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To develop methods guidance to support the conduct of rapid reviews (RRs) produced within Cochrane and beyond, in response to requests for timely evidence syntheses for decision-making purposes including urgent health issues of high priority. STUDY DESIGN AND SETTING: Interim recommendations were informed by a scoping review of the underlying evidence, primary methods studies conducted, and a survey sent to 119 representatives from 20 Cochrane entities, who were asked to rate and rank RR methods across stages of review conduct. Discussions among those with expertise in RR methods further informed the list of recommendations with accompanying rationales provided. RESULTS: Based on survey results from 63 respondents (53% response rate), 26 RR methods recommendations are presented for which there was a high or moderate level of agreement or scored highest in the absence of such agreement. Where possible, how recommendations align with Cochrane methods guidance for systematic reviews is highlighted. CONCLUSION: The Cochrane Rapid Reviews Methods Group offers new, interim guidance to support the conduct of RRs. Because best practice is limited by the lack of currently available evidence for some RR methods shortcuts taken, this guidance will need to be updated as additional abbreviated methods are evaluated.

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)0.855
metaresearch head score (Gemma)0.979
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8550.979
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0450.016
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0060.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.008

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 head0.971
GPT teacher head0.751
Teacher spread0.220 · 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