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Record W4401893139 · doi:10.1002/ase.2500

Journal recommended guidelines for systematic review and meta‐analyses

2024· article· en· W4401893139 on OpenAlexaff
Adam B. Wilson, Boon‐Huat Bay, Jessica N. Byram, Melissa A. Carroll, Gabrielle M. Finn, Niels Hammer, Sabine Hildebrandt, Claudia Krebs, Jonathan J. Wisco, Jason M. Organ

Bibliographic record

VenueAnatomical Sciences Education · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMEDLINEMeta-analysisMedical educationPsychologyMedicineChemistryPathology

Abstract

fetched live from OpenAlex

Systematic reviews and meta-analyses aggregate research findings across studies and populations, making them a valuable form of research evidence. Over the past decade, studies in medical education using these methods have increased by 630%. However, many manuscripts are not publication-ready due to inadequate planning and insufficient analyses. These guidelines aim to improve the clarity and comprehensiveness of reporting methodologies and outcomes, ensuring high quality and comparability. They align with existing standards like PRISMA, providing examples and best practices. Adhering to these guidelines is crucial for publication consideration in Anatomical Sciences Education.

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 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)0.129
metaresearch head score (Gemma)0.095
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1290.095
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.898
GPT teacher head0.682
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2024
Admission routes1
Has abstractyes

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