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Record W2100446258 · doi:10.1136/bmjqs.2010.043257

Guideline adaptation: an approach to enhance efficiency in guideline development and improve utilisation

2011· article· en· W2100446258 on OpenAlexafffund
Béatrice Fervers, Jako Burgers, Rachel Voellinger, Melissa Brouwers, George P. Browman, Ian D. Graham, M B Harrison, Jean Latreille, Najoua Mlika-Cabane, Louise Paquet, Louise Zitzelsberger, Bernard Burnand

Bibliographic record

VenueBMJ Quality & Safety · 2011
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHôpital Charles-Le MoyneMinistère de la Santé et des Services Sociaux (Québec)Canadian Institutes of Health ResearchBC Cancer AgencyUniversité de SherbrookeQueen's UniversityCancer Care OntarioMcMaster UniversityUniversity of OttawaCanadian Partnership Against Cancer
FundersCanadian Institutes of Health Research
KeywordsGuidelineAdaptation (eye)Process (computing)Process managementQuality (philosophy)RigourSet (abstract data type)MedicineComputer sciencePsychologyEngineeringPathology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.233
metaresearch head score (Gemma)0.294
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.767
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2330.294
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0140.011
Science and technology studies0.0050.006
Scholarly communication0.0140.012
Open science0.0070.021
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0060.004

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 head0.378
GPT teacher head0.526
Teacher spread0.148 · 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 designTheoretical or conceptual
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

Citations267
Published2011
Admission routes2
Has abstractyes

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