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Record W2755459284 · doi:10.1016/j.eururo.2017.08.016

Key Steps in Conducting Systematic Reviews for Underpinning Clinical Practice Guidelines: Methodology of the European Association of Urology

2017· article· en· W2755459284 on OpenAlexaff
Thomas Knoll, Muhammad Imran Omar, Steven MacLennan, Virginia Hernández, Steven E. Canfield, Yuhong Yuan, Max Bruins, Lorenzo Marconi, James N’Dow, Richard Sylvester

Bibliographic record

VenueEuropean Urology · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineSystematic reviewUnderpinningMEDLINEEvidence-based medicineRandomized controlled trialAlternative medicineSurgeryPathology

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)0.739
metaresearch head score (Gemma)0.844
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.261
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7390.844
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0130.014
Bibliometrics0.0230.020
Science and technology studies0.0050.009
Scholarly communication0.0200.011
Open science0.0090.014
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0070.003

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 head0.952
GPT teacher head0.659
Teacher spread0.293 · 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 designNot applicable
DomainMethods
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

Citations226
Published2017
Admission routes1
Has abstractno

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