MétaCan
Menu
Back to cohort
Record W3203243032 · doi:10.1186/s13643-021-01821-3

Scoping reviews: reinforcing and advancing the methodology and application

2021· article· en· W3203243032 on OpenAlexafffund
Micah D.J. Peters, Casey Marnie, Heather Colquhoun, Chantelle Garritty, Susanne Hempel, Tanya Horsley, Étienne V Langlois, Erin Lillie, Kelly K. O’Brien, Özge Tunçalp, Michael G. Wilson, Wasifa Zarin, Andrea C. Tricco

Bibliographic record

VenueSystematic Reviews · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsSt. Michael's HospitalQueen's UniversityMcMaster UniversityImpactToronto Rehabilitation InstituteSunnybrook Health Science CentreRoyal College of Physicians and Surgeons of CanadaInstitute for Work & HealthOttawa HospitalUniversity of Toronto
FundersCanada Research ChairsWorld Health Organization
KeywordsSystematic reviewRigourTerminologyCLARITYMedicinePresentation (obstetrics)StakeholderManagement scienceConsistency (knowledge bases)Process managementMEDLINEComputer scienceEngineeringPublic relations

Abstract

fetched live from OpenAlex

Scoping reviews are an increasingly common approach to evidence synthesis with a growing suite of methodological guidance and resources to assist review authors with their planning, conduct and reporting. The latest guidance for scoping reviews includes the JBI methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Extension for Scoping Reviews. This paper provides readers with a brief update regarding ongoing work to enhance and improve the conduct and reporting of scoping reviews as well as information regarding the future steps in scoping review methods development. The purpose of this paper is to provide readers with a concise source of information regarding the difference between scoping reviews and other review types, the reasons for undertaking scoping reviews, and an update on methodological guidance for the conduct and reporting of scoping reviews.Despite available guidance, some publications use the term 'scoping review' without clear consideration of available reporting and methodological tools. Selection of the most appropriate review type for the stated research objectives or questions, standardised use of methodological approaches and terminology in scoping reviews, clarity and consistency of reporting and ensuring that the reporting and presentation of the results clearly addresses the review's objective(s) and question(s) are critical components for improving the rigour of scoping reviews.Rigourous, high-quality scoping reviews should clearly follow up to date methodological guidance and reporting criteria. Stakeholder engagement is one area where further work could occur to enhance integration of consultation with the results of evidence syntheses and to support effective knowledge translation. Scoping review methodology is evolving as a policy and decision-making tool. Ensuring the integrity of scoping reviews by adherence to up-to-date reporting standards is integral to supporting well-informed decision-making.

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)0.589
metaresearch head score (Gemma)0.688
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.411
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5890.688
Meta-epidemiology (narrow)0.0040.006
Meta-epidemiology (broad)0.0090.008
Bibliometrics0.0440.044
Science and technology studies0.0090.038
Scholarly communication0.0500.047
Open science0.0100.042
Research integrity0.0190.032
Insufficient payload (model declined to judge)0.0160.016

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 head0.474
GPT teacher head0.575
Teacher spread0.101 · 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
GenreMethods

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

Citations834
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueSystematic ReviewsSame topicEvaluation and Performance AssessmentFrench-language works237,207