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Record W2303709641

Impact of family medicine research: Bibliometrics and beyond.

2016· article· en· W2303709641 on OpenAlexaff
Lynn Dunikowski, Thomas R. Freeman

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsWestern UniversityCollege of Family Physicians of Canada
Fundersnot available
KeywordsBibliometricsLegitimacyWork (physics)Academic medicineSocial scienceSociologyEngineering ethicsPolitical scienceMedicineMedical educationLibrary scienceEngineeringLawComputer science
DOInot available

Abstract

fetched live from OpenAlex

A discipline is defined by an active area of research and a codified body of knowledge[1][1],[2][2] that provides legitimacy for the work it does and leads to innovation. Academic family medicine has existed for almost 50 years. Family medicine research has made great strides,[3][3] with a steady

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometricsMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.038
metaresearch head score (Gemma)0.250
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.250
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.1180.192
Science and technology studies0.0010.002
Scholarly communication0.0090.009
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.428
GPT teacher head0.548
Teacher spread0.120 · 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

Labeled directly by 2 models reading the full record.

BibliometricsMetaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational
DomainEvaluation
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

Citations16
Published2016
Admission routes1
Has abstractyes

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Same venuePubMedSame topicPrimary Care and Health OutcomesCategoryBibliometricsFrench-language works237,207