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A third of systematic reviews changed or did not specify the primary outcome: a PROSPERO register study

2016· article· en· W2332511819 on OpenAlexafffund
Andrea C. Tricco, Elise Cogo, Matthew J. Page, Julie Polisena, Alison Booth, Kerry Dwan, H. Robson MacDonald, Tammy Clifford, Lesley Stewart, Sharon E. Straus, David Moher

Bibliographic record

VenueJournal of Clinical Epidemiology · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa HospitalCanadian Agency for Drugs and Technologies in HealthCanada Research ChairsUniversity of OttawaUniversity of TorontoSt. Michael's Hospital
FundersNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsRegister (sociolinguistics)Outcome (game theory)MedicineFamily medicineLinguisticsMathematicsPhilosophy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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
gemmaMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.179
metaresearch head score (Gemma)0.475
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.946

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1790.475
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0100.020
Bibliometrics0.0130.017
Science and technology studies0.0030.003
Scholarly communication0.0060.006
Open science0.0030.005
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.973
GPT teacher head0.702
Teacher spread0.271 · 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

Labeled directly by 2 models reading the full record.

Study designObservational
DomainReporting
GenreEmpirical

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

Citations75
Published2016
Admission routes2
Has abstractno

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Same venueJournal of Clinical EpidemiologySame topicMeta-analysis and systematic reviewsCategoryMetaresearchFrench-language works237,207