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Record W2993226818

Evaluating best practice guidelines.

2005· article· en· W2993226818 on OpenAlexaffabout
Nancy Edwards, Barbara Davies, Jenny Ploeg, Maureen Dobbins, Jennifer Skelly, Pat Griffin, Sylvia Ralphs‐Thibodeau

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBest practiceNursing practiceHealth careClinical PracticeNursingProcess (computing)MedicineMedical educationComputer sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Clinical practice guidelines are developed with the purpose of improving patient care. The Registered Nurses Association of Ontario (RNAO) Nursing Best Practice Guidelines (BPG) Project was implemented in 1999. It has resulted in the development, implementation and evaluation of 17 BPGs with agencies in different healthcare sectors. This article describes the process, challenges and lessons learned by the team responsible for evaluating the BPGs.

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)0.391
metaresearch head score (Gemma)0.652
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.609
Threshold uncertainty score0.751

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3910.652
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0130.010
Science and technology studies0.0030.002
Scholarly communication0.0090.007
Open science0.0040.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.004

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 head0.611
GPT teacher head0.592
Teacher spread0.019 · 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
DomainEvaluation
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

Citations20
Published2005
Admission routes2
Has abstractyes

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