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Record W1967135833 · doi:10.1136/bmj.329.7456.39-a

Decision aids in clinical practice

2004· article· en· W1967135833 on OpenAlexaff
Ann Cranney

Bibliographic record

VenueBMJ · 2004
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsDecision aidsAppealDecision analysisMedicineAdjunctDecision processClinical decision makingDecision support systemPsychologyManagement scienceFamily medicineComputer scienceAlternative medicinePolitical scienceData miningEngineering

Abstract

fetched live from OpenAlex

Decision aids can be a useful format to communicate evidence based information on harms and benefits of therapies to individual patients. When used as an adjunct to the consultation, decision aids can change the format of the consultation process; decision aids are designed to enhance communication and interaction between patient and practitioner—not to replace it. Decision aids are not indicated for each clinical decision or scenario and they may not appeal to all physicians. But trials evaluating decision aids in the United Kingdom concluded that they helped patients use information to clarify …

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)0.075
metaresearch head score (Gemma)0.298
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.298
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.010
Science and technology studies0.0030.012
Scholarly communication0.0210.015
Open science0.0040.010
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0730.029

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 head0.409
GPT teacher head0.602
Teacher spread0.193 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations2
Published2004
Admission routes1
Has abstractyes

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