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Record W2107641617

Canadian Quality Circle pilot project in osteoporosis: rationale, methods, and feasibility.

2007· article· en· W2107641617 on OpenAlexaffabout
George Ioannidis, Αλεξάνδρα Παπαϊωάννου, Lehana Thabane, Amiram Gafni, Anthony B. Hodsman, Brent Kvern, D Johnstone, Nathalie Plumley, Alanna Baldwin, Malcolm Doupe, Alan Katz, Lena Salach, Jonathan D. Adachi

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineIntervention (counseling)OsteoporosisQuality (philosophy)Baseline (sea)Data collectionWork (physics)Family medicineMedical educationNursingEngineeringPathology
DOInot available

Abstract

fetched live from OpenAlex

UNLABELLED: PROBLEM ADDRESSED Family physicians are not adequately following the 2002 Osteoporosis Canada guidelines for providing optimal care to patients with osteoporosis. OBJECTIVE OF PROGRAM: The Canadian Quality Circle (CQC) pilot project was developed to assess the feasibility of the CQC project design and to gather information for implementing a national study of quality circles (QCs). The national study would assess whether use ofQCs could improve family physicians' adherence to the osteoporosis guidelines. PROGRAM DESCRIPTION: The pilot project enrolled 52 family physicians and involved 7 QCs. The project had 3 phases: training and baseline data collection, educational intervention and follow-up data collection, and sessions on implementing strategies for care. CONCLUSION: Findings from the pilot study showed that the CQC project was well designed and well received. Use of QCs appeared to be feasible for transferring knowledge and giving physicians an opportunity to analyze work-related problems and develop solutions to them.

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)0.042
metaresearch head score (Gemma)0.030
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: none
Teacher disagreement score0.481
Threshold uncertainty score0.957

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0010.001
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.141
GPT teacher head0.432
Teacher spread0.292 · 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

Citations7
Published2007
Admission routes2
Has abstractyes

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Same venuePubMed→Same topicBone health and osteoporosis research→French-language works237,207→