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Record W1499421601 · doi:10.17269/cjph.105.4039

A vision for chronic disease prevention and intervention research: Report from a workshop

2014· article· en· W1499421601 on OpenAlexaffvenue
Fredrick D. Ashbury, Julian Little, John P. A. Ioannidis, Nancy Kreiger, Lyle J. Palmer, Clare Relton, Peter Taylor

Bibliographic record

VenueCanadian Journal of Public Health · 2014
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsOntario Institute for Cancer ResearchLunenfeld-Tanenbaum Research InstituteCancer Care OntarioUniversity of OttawaUniversity of CalgaryPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsIntervention (counseling)Session (web analytics)StakeholderMedical educationPopulationScale (ratio)Stakeholder engagementResearch designImplementation researchPsychologyTranslational researchMedicinePublic relationsManagement sciencePsychological interventionEngineeringNursingComputer sciencePolitical scienceSociologyEnvironmental health

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.154
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.817

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1540.072
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0030.002
Science and technology studies0.0140.012
Scholarly communication0.0200.012
Open science0.0070.029
Research integrity0.0410.051
Insufficient payload (model declined to judge)0.0060.002

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 head0.170
GPT teacher head0.457
Teacher spread0.287 · 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.

Study designNot applicable
DomainMethods
GenreReview

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

Citations5
Published2014
Admission routes2
Has abstractno

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