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Record W2118923642 · doi:10.2337/dc06-1654

Diabetes Is Not Treated as a Coronary Artery Disease Risk Equivalent

2007· article· en· W2118923642 on OpenAlexafffund
Baiju R. Shah, Janet E. Hux, Peter C. Austin

Bibliographic record

VenueDiabetes Care · 2007
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsMedicineDiabetes mellitusMyocardial infarctionInternal medicineCoronary artery diseaseObservational studyRisk factorDiseaseBlood pressureEmergency medicineCardiologyEndocrinology

Abstract

fetched live from OpenAlex

O bservational studies (1–3) havesuggested that the risk of mortalityis equivalent for patients with myo-cardial infarction (MI) without previous diabetes and for diabetic patients without previous MI. Because vascular risk-reduction targets are based on a patient’s future risk, clinical practice guidelines (4–9) recommend that the same or lower blood pressure and lipid targets be ap-plied to diabetic patients as would be ap-plied for secondary prevention following MI. Patients newly diagnosed with diabe-tes and those with first MIs enter a high-risk category for subsequent coronary events. Therefore, if diabetes were treated as a coronary artery disease risk equiva-

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)0.001
metaresearch head score (Gemma)0.006
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: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.020
GPT teacher head0.302
Teacher spread0.282 · 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
GenreCommentary

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

Citations10
Published2007
Admission routes2
Has abstractyes

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