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Record W7096356106

Clinical Review

2016· article· en· W7096356106 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Inclusion (mineral)Alternative medicineClinical PracticeFamily studiesValue (mathematics)Research council
DOInot available

Abstract

fetched live from OpenAlex

Objective To identify 10 noteworthy Canadian family medicine research studies that have affected practice in order to demonstrate the unique value that Canadian family medicine research offers. Composition of the committee Representatives from the Section of Researchers (SOR) and the Health Policy and Government Relations department of the College of Family Physicians of Canada developed a framework for inclusion and identified an initial list of articles. Members of the SOR Council and research directors from the 17 Canadian departments of family medicine reviewed the preliminary list and suggested additional studies. Methods The authors developed an initial list of studies carried out by Canadian family medicine researchers from those researchers who had received awards from the College of Family Physicians of Canada since 2002. Additional studies were proposed by members of the SOR Council and the university research directors. A total of 36 published articles were reviewed by the SOR authors, and an annotated short list of 16 articles was prepared. From that list, the other authors identified 7 noteworthy studies that were used to form the basis of advocacy materials.

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)0.006
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0530.016

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 head0.563
GPT teacher head0.656
Teacher spread0.093 · 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
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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