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Record W2911253631 · doi:10.22374/cjgim.v14i1.318

BMJ Rapid Recommendations: Creating Tools to Support a Revolution in Clinical Practice Guideline Adoption

2019· article· en· W2911253631 on OpenAlexaffvenue
Gordon Guyatt, Thomas Agoritsas, Lyubov Lytvyn, Reed Siemieniuk, Per Olav Vandvik

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineClinical PracticeTrustworthinessFamily medicineInternet privacy

Abstract

fetched live from OpenAlex

BMJ rapid recommendations hold the potential to revolutionize clinical practice guidelines, achieving both timeliness, trustworthiness, and usefulness to clinicians and patients to allow well informed decisions in clinical practice.

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)0.249
metaresearch head score (Gemma)0.714
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2490.714
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0180.016
Science and technology studies0.0050.005
Scholarly communication0.0230.023
Open science0.0060.021
Research integrity0.0220.021
Insufficient payload (model declined to judge)0.0640.057

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 head0.254
GPT teacher head0.536
Teacher spread0.282 · 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

Citations13
Published2019
Admission routes2
Has abstractyes

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