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Record W2156536461 · doi:10.3122/jabfm.2009.04.090105

Practice-based Research is Community Engagement

2009· article· en· W2156536461 on OpenAlexaff
John M. Westfall, Lyle J. Fagnan, Margaret A. Handley, Jon Salsberg, Paul McGinnis, Linda Zittleman, Ann C. Macaulay

Bibliographic record

VenueThe Journal of the American Board of Family Medicine · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineCommunity engagementMedical educationCommunity healthTranslational researchTranslational scienceEngineering ethicsPublic relationsNursingPublic healthPathology

Abstract

fetched live from OpenAlex

Community engagement has become a major contributor to medical research during the past 10 years and is an essential component of the current National Institutes of Health (NIH) Roadmap and the Clinical and Translational Science Awards program.[1][1][,2][2] But, what is a community? And what

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)0.162
metaresearch head score (Gemma)0.259
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.857

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1620.259
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.006
Science and technology studies0.0080.037
Scholarly communication0.0230.024
Open science0.0040.026
Research integrity0.0130.016
Insufficient payload (model declined to judge)0.0210.004

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 head0.475
GPT teacher head0.575
Teacher spread0.100 · 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 designTheoretical or conceptual
DomainMethods
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

Citations85
Published2009
Admission routes1
Has abstractyes

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