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Pharmacist and family physician collaboration to optimize community-based drug therapy: Results of a 15-year research program

2007· article· en· W1994701925 on OpenAlexvenueaboutno aff
Laurie A. Dunn, Nicola J. Pilla

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacistDrugMedicineFamily medicinePsychiatryPharmacy

Abstract

fetched live from OpenAlex

Project Objective:This research program was initiated in 1992 in Ontario to improve drug therapy in the community by providing access to independent information about drugs to both primary care providers and patients. The first major initiative was the development and distribution of the Anti-infective Guidelines for Community-acquired Infections. The program has evolved and expanded nationally to provide evidence-based prescribing materials and interdisciplinary continuing professional development (CPD) on a number of common topics.Target Groups:All community-based primary health care professionals, including pharmacists, physicians, and nurse practitioners.Activities:A number of activities were undertaken and evaluated over the last 15 years, including academic detailing (5 studies), drug regimen review, clinical practice guideline (CPG) development and distribution and MAINPRO-C accredited CPD featuring a small group, case-based learning model with pharmacist-physician facilitator team delivery. The ou...

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)0.023
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.252
GPT teacher head0.507
Teacher spread0.254 · 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 designObservational
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

Citations0
Published2007
Admission routes2
Has abstractyes

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