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Primary Prevention of Cardiovascular Diseases in People With Diabetes Mellitus

2006· article· en· W2161474086 on OpenAlexaff
John B. Buse, Henry N. Ginsberg, George L. Bakris, Nathaniel G. Clark, Fernando Costa, Robert H. Eckel, Vivian Fonseca, Hertzel C. Gerstein, Scott M. Grundy, Richard W. Nesto, Michael Pignone, Jorge Plutzky, Daniel Porte, Rita F. Redberg, Kimberly F. Stitzel, Neil J. Stone

Bibliographic record

VenueCirculation · 2006
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsMedicineDiabetes mellitusPrimary preventionDiseaseStatement (logic)Family medicineIntensive care medicineGerontologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The American Heart Association (AHA) and the American Diabetes Association (ADA) have each published guidelines for cardiovascular disease prevention: The ADA has issued separate recommendations for each of the cardiovascular risk factors in patients with diabetes, and the AHA has shaped primary and secondary guidelines that extend to patients with diabetes. This statement will attempt to harmonize the recommendations of both organizations where possible but will recognize areas in which AHA and ADA recommendations differ.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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
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

Citations637
Published2006
Admission routes1
Has abstractyes

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