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Record W2765072958 · doi:10.12927/hcq.2016.24700

It Takes Two to Tango: Researchers and Decision-Makers Collaborating to Implement Practice Changes for Patients with Multimorbidity

2016· article· en· W2765072958 on OpenAlexaffabout
Martin Fortin, Martine Couture, Tarek Bouhali, Esther Leclerc, Moira Stewart

Bibliographic record

VenueHealthcare Quarterly · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsWestern UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
Fundersnot available
KeywordsBest practiceBusinessPublic relationsMedical educationMedicineNursingProcess managementPolitical scienceManagementEconomics

Abstract

fetched live from OpenAlex

An integrated knowledge translation strategy is a key factor in fostering the implementation of practice changes. Building on a 15-year history of projects that include close collaboration between researchers and decision-makers in the Saguenay region of Quebec (Canada), the authors identify several key elements that resulted in practice changes in primary care and improved outcomes for patients with multimorbidity.

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)0.155
metaresearch head score (Gemma)0.268
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.155
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1550.268
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0050.004
Science and technology studies0.0360.022
Scholarly communication0.0530.036
Open science0.0070.038
Research integrity0.0380.041
Insufficient payload (model declined to judge)0.0170.009

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 head0.079
GPT teacher head0.442
Teacher spread0.363 · 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 designQualitative
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

Citations14
Published2016
Admission routes2
Has abstractyes

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