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Record W2126384096 · doi:10.1016/j.ahj.2013.03.018

Rationale and design of the Cardiovascular Inflammation Reduction Trial: A test of the inflammatory hypothesis of atherothrombosis

2013· article· en· W2126384096 on OpenAlexaff
Brendan M. Everett, Aruna D. Pradhan, Daniel H. Solomon, Nina P. Paynter, Jean MacFadyen, Elaine Zaharris, Milan Gupta, Michael Clearfield, Peter Libby, Ahmed Hasan, Robert J. Glynn, Paul M. Ridker

Bibliographic record

VenueAmerican Heart Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsCanadian Respiratory Research NetworkUniversity of Toronto
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicineHeart failureInternal medicineMyocardial infarctionClinical endpointAcute coronary syndromeDiabetes mellitusType 2 diabetesCardiologyRheumatoid arthritisPlaceboClinical trialPathologyEndocrinology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.069
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.069
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.069
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0100.004

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 head0.028
GPT teacher head0.248
Teacher spread0.219 · 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 designTheoretical or conceptual
Domainnot available
GenreProtocol

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

Citations365
Published2013
Admission routes1
Has abstractno

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