MétaCan
Menu
Back to cohort
Record W3139314136 · doi:10.1111/hir.12367

Adoption of peer review of literature search strategies in knowledge synthesis from 2009 to 2018: An overview

2021· review· en· W3139314136 on OpenAlex
Christine Neilson

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Information & Libraries Journal · 2021
Typereview
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsScopusPeer reviewCitationInclusion (mineral)Grey literatureSystematic reviewQuality (philosophy)MEDLINEComputer scienceMedicinePsychologyMedical educationLibrary sciencePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge synthesis (KS) reviews rely on good quality literature searches to capture a complete set of relevant studies, and peer review of the search strategy is one quality control mechanism that contributes to better quality reviews. Guidelines for peer review of electronic search strategies (PRESS) have been available since 2008. OBJECTIVES: This overview provides a snapshot of KS indexed in Scopus, published between 2009 and 2018, that reported peer review of the literature search strategy. METHODS: Articles were identified through citation chasing for PRESS guidance documents and supplementary keyword searches. The characteristics of individual articles and the journals that published them were documented, and descriptive statistics were compiled. RESULTS: 415 articles from 169 journals met inclusion criteria. Approximately half were published in 14 journal titles. Most reviews reported the involvement of an information professional, but PRESS reviewers were rarely acknowledged. An overwhelming majority of review teams were based in Canada. DISCUSSION: Reported use of PRESS was low during the period examined, but under-reporting may be a factor. Investigation of the barriers and facilitators of PRESS adoption is needed. CONCLUSION: Despite its value, adoption of PRESS appears low. Advocacy for, and education about, PRESS may be required.

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)0.043
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0480.140
Science and technology studies0.0000.000
Scholarly communication0.0050.011
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.716
GPT teacher head0.621
Teacher spread0.095 · 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