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Record W2143883401 · doi:10.1136/bmj.g7624

Decision aids that really promote shared decision making: the pace quickens

2015· article· en· W2143883401 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsMcMaster UniversityHamilton General Hospital
FundersNational Center for Advancing Translational SciencesInstituto de Salud Carlos IIISykehuset Innlandet HFHelse Sør-Øst RHFAcademy of FinlandEuropean CommissionNational Science FoundationJane ja Aatos Erkon SäätiöSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPaceR-CASTPoint (geometry)Decision aidsClinical decision makingPsychologyBusiness decision mappingManagement scienceComputer scienceRisk analysis (engineering)Decision support systemMedicineEngineeringArtificial intelligenceIntensive care medicineAlternative medicineGeography

Abstract

fetched live from OpenAlex

Decision aids can help shared decision making, but most have been hard to produce, onerous to update, and are not being used widely. <b>Thomas Agoritsas and colleagues</b> explore why and describe a new electronic model that holds promise of being more useful for clinicians and patients to use together at the point of care

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.354
GPT teacher head0.493
Teacher spread0.139 · 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