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Record W2156098321 · doi:10.1136/bmj.b2535

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

2009· article· en· W2156098321 on OpenAlexafffund
David Moher, A. Liberati, Jennifer Tetzlaff, Douglas G. Altman

Bibliographic record

VenueBMJ · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersMedical Research CouncilCare and Public Health Research Institute, Universiteit MaastrichtHealth Services Research and DevelopmentCanadian Institutes of Health ResearchJohns Hopkins Bloomberg School of Public HealthCancer Research UKMcMaster UniversityOttawa Hospital Research InstituteJohns Hopkins UniversityUniversity of IoanninaGlaxoSmithKlineUniversity of BernUniversity of Ottawa
KeywordsSystematic reviewStatement (logic)Computer scienceInformation retrievalData scienceMEDLINEMedicineWorld Wide WebBiologyPolitical science

Abstract

fetched live from OpenAlex

David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

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)0.140
metaresearch head score (Gemma)0.416
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score0.741

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1400.416
Meta-epidemiology (narrow)0.0090.009
Meta-epidemiology (broad)0.0340.036
Bibliometrics0.0300.035
Science and technology studies0.0040.007
Scholarly communication0.0090.008
Open science0.0140.008
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0880.017

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 head0.946
GPT teacher head0.655
Teacher spread0.291 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReporting
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

Citations83,276
Published2009
Admission routes2
Has abstractyes

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