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Record W4281647098 · doi:10.1002/leap.1463

The <scp>AMSTAR</scp>‐2 critical appraisal tool and editorial decision‐making for systematic reviews: Retrospective, bibliometric study

2022· article· en· W4281647098 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.

Bibliographic record

VenueLearned Publishing · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsOperationalizationSystematic reviewStrengths and weaknessesMedicineCritical appraisalRetrospective cohort studyMEDLINEFamily medicinePsychologyPathologyAlternative medicineSocial psychologyPolitical sciencePhysicsLaw

Abstract

fetched live from OpenAlex

Abstract AMSTAR‐2 is a critical appraisal instrument for systematic reviews and may have a role in editorial processes. This study explored whether associations exist between AMSTAR‐2 assessments and editorial decisions. A retrospective, cross‐sectional study of manuscripts submitted to a single journal between 2015 and 2017 was undertaken. All submissions that reported an eligible systematic review were assessed using AMSTAR‐2 by two assessors. Inter‐rater agreement (IRR) was calculated for all AMSTAR‐2 items. Associations between AMSTAR‐2 assessments and the editorial decision, final publication status in any journal, and measures of impact were explored. One hundred and twenty‐two manuscripts were included. Across all AMSTAR‐2 items, the IRR varied from 0.03 (slight agreement) to 0.82 (substantial agreement). All submissions contained at least two critical methodological weaknesses. There was no difference in the number of weaknesses (median: 4; IQR: 3–5 vs. median: 4; IQR: 3.5–4.5; p = 0.482) between accepted and rejected submissions. Neither was there a difference between rejected submissions published elsewhere and those which remained unpublished (median: 4; IQR: 3.5–4.5 vs. median: 4; IQR: 4.5–5; p = 0.103). The number of weaknesses was not associated with academic impact. There was no association with AMSTAR‐2 assessments and editorial outcomes. Further work is required to explore whether the instrument can be prospectively operationalized for use during editorial processes.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchBibliometrics
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchBibliometrics
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.439
metaresearch head score (Gemma)0.927
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4390.927
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0100.054
Science and technology studies0.0030.000
Scholarly communication0.0350.003
Open science0.0050.002
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 head0.476
GPT teacher head0.526
Teacher spread0.050 · 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