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World Health Organization strong recommendations based on low-quality evidence (study quality) are frequent and often inconsistent with GRADE guidance

2014· review· en· W1977498299 on OpenAlexaff
Paul Alexander, Juan P. Brito, Ignacio Neumann, Michael R. Gionfriddo, Lisa Bero, Benjamin Djulbegović, Rebecca J. Stoltzfus, Víctor M. Montori, Susan L. Norris, Holger J. Schünemann, Gordon Guyatt

Bibliographic record

VenueJournal of Clinical Epidemiology · 2014
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHealth Sciences CentreMcMaster University
FundersWorld Health Organization
KeywordsMedicineGuidelineConfidence intervalMEDLINEQuality of evidenceEvidence-based medicineFamily medicinePsychological interventionEvidence-based practicePublic healthMeta-analysisAlternative medicineNursingPathology

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

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)0.193
metaresearch head score (Gemma)0.583
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.807
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1930.583
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0110.013
Bibliometrics0.0140.008
Science and technology studies0.0020.004
Scholarly communication0.0090.007
Open science0.0070.005
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0060.001

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 head0.835
GPT teacher head0.704
Teacher spread0.131 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainEvaluation
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

Citations84
Published2014
Admission routes1
Has abstractno

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