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Record W2544262221 · doi:10.1186/s13643-016-0360-z

Cochrane Rapid Reviews Methods Group to play a leading role in guiding the production of informed high-quality, timely research evidence syntheses

2016· article· en· W2544262221 on OpenAlexaff
Chantelle Garritty, Adrienne Stevens, Gerald Gartlehner, Valerie King, Chris Kamel

Bibliographic record

VenueSystematic Reviews · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCanadian Agency for Drugs and Technologies in HealthOttawa Hospital
Fundersnot available
KeywordsSystematic reviewTimelineMedicineTransparency (behavior)Health careQuality (philosophy)Evidence-based medicineEvidence-based practiceManagement scienceProcess managementMEDLINEKnowledge managementAlternative medicineComputer scienceBusinessPolitical scienceEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Policymakers and healthcare stakeholders are increasingly seeking evidence to inform the policymaking process, and often use existing or commissioned systematic reviews to inform decisions. However, the methodologies that make systematic reviews authoritative take time, typically 1 to 2 years to complete. Outside the traditional SR timeline, "rapid reviews" have emerged as an efficient tool to get evidence to decision-makers more quickly. However, the use of rapid reviews does present challenges. To date, there has been limited published empirical information about this approach to compiling evidence. Thus, it remains a poorly understood and ill-defined set of diverse methodologies with various labels. In recent years, the need to further explore rapid review methods, characteristics, and their use has been recognized by a growing network of healthcare researchers, policymakers, and organizations, several with ties to Cochrane, which is recognized as representing an international gold standard for high-quality, systematic reviews. PURPOSE: In this commentary, we introduce the newly established Cochrane Rapid Reviews Methods Group developed to play a leading role in guiding the production of rapid reviews given they are increasingly employed as a research synthesis tool to support timely evidence-informed decision-making. We discuss how the group was formed and outline the group's structure and remit. We also discuss the need to establish a more robust evidence base for rapid reviews in the published literature, and the importance of promoting registration of rapid review protocols in an effort to promote efficiency and transparency in research. CONCLUSION: As with standard systematic reviews, the core principles of evidence-based synthesis should apply to rapid reviews in order to minimize bias to the extent possible. The Cochrane Rapid Reviews Methods Group will serve to establish a network of rapid review stakeholders and provide a forum for discussion and training. By facilitating exchange, the group will strive to conduct research to advance the methods of rapid reviews.

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)0.430
metaresearch head score (Gemma)0.753
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.570
Threshold uncertainty score0.704

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4300.753
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0170.017
Bibliometrics0.0330.026
Science and technology studies0.0050.016
Scholarly communication0.0370.023
Open science0.0170.019
Research integrity0.0360.045
Insufficient payload (model declined to judge)0.0480.050

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 head0.895
GPT teacher head0.657
Teacher spread0.238 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
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

Citations76
Published2016
Admission routes1
Has abstractyes

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