MétaCan
Menu
Back to cohort
Record W4220744986 · doi:10.11124/jbies-21-00483

What are scoping reviews? Providing a formal definition of scoping reviews as a type of evidence synthesis

2022· article· en· W4220744986 on OpenAlexaff

Bibliographic record

VenueJBI Evidence Synthesis · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsPublic Health OntarioUniversity of TorontoSt. Michael's HospitalQueen's University
Fundersnot available
KeywordsSystematic reviewKey (lock)Empirical evidenceFormal concept analysisIdentification (biology)Context (archaeology)

Abstract

fetched live from OpenAlex

ABSTRACT: Evidence synthesis encompasses a broad range of review types, and scoping reviews are an increasingly popular approach to synthesizing evidence in a number of fields. They sit alongside other evidence synthesis methodologies, such as systematic reviews, qualitative evidence synthesis, realist synthesis, and many more. Until now, scoping reviews have been variously defined in the literature. In this article, we provide the following formal definition for scoping reviews: Scoping reviews are a type of evidence synthesis that aims to systematically identify and map the breadth of evidence available on a particular topic, field, concept, or issue, often irrespective of source (ie, primary research, reviews, non-empirical evidence) within or across particular contexts. Scoping reviews can clarify key concepts/definitions in the literature and identify key characteristics or factors related to a concept, including those related to methodological research.

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)0.371
metaresearch head score (Gemma)0.644
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.629
Threshold uncertainty score0.776

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3710.644
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0090.009
Bibliometrics0.0350.040
Science and technology studies0.0060.027
Scholarly communication0.0400.036
Open science0.0080.015
Research integrity0.0220.014
Insufficient payload (model declined to judge)0.0080.006

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 head0.760
GPT teacher head0.530
Teacher spread0.230 · 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 designTheoretical or conceptual
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

Citations616
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJBI Evidence SynthesisSame topicMeta-analysis and systematic reviewsFrench-language works237,207