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Record W2993781226 · doi:10.1503/cmaj.191362

Strategic Clinical Networks

2019· article· en· W2993781226 on OpenAlexaffvenueabout
Tracy Wasylak, Allison Strilchuk, Braden Manns

Bibliographic record

VenueCanadian Medical Association Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsLibin Cardiovascular Institute of AlbertaAlberta HealthUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsKey (lock)Computer scienceScale (ratio)Process managementTest (biology)Data scienceHealth careKnowledge managementBusinessComputer securityPolitical scienceGeography

Abstract

fetched live from OpenAlex

KEY POINTS Alberta first piloted Strategic Clinical Networks (SCNs) in 2012 and has leveraged them as a way to get evidence into care, rapidly test and scale proven health innovations, and bring stakeholders and health partners together to achieve common goals. For 7 years, SCNs have catalyzed

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)0.059
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.978
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0110.005
Open science0.0030.013
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0890.019

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 head0.137
GPT teacher head0.455
Teacher spread0.319 · 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
GenreCommentary

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

Citations17
Published2019
Admission routes3
Has abstractyes

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