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Impact of Complete Revascularization in the ISCHEMIA Trial
Gregg W. Stone, Ziad A. Ali, Sean M. O’Brien, Grace L. Rhodes, Philippe Généreux, Sripal Bangalore, Kreton Mavromatis, Jennifer Horst, Ovidiu Dressler, Kian Keong Poh, Ranjit Kumar Nath, Nagaraja Moorthy, Adam Witkowski, Sudhanshu Kumar Dwivedi, O.L. Bockeria, Jiyan Chen, Paola Smanio, Michael H. Picard, Bernard Chaitman, Daniel S. Berman, Leslee J. Shaw, William E. Boden, Harvey D. White, Stephen E. Fremes, Yves Rosenberg, Harmony R. Reynolds, John A. Spertus, Judith S. Hochman, David J. Maron, Robert A. Harrington, David O. Williams, Karen P. Alexander, Jeffrey S. Berger, Daniel B. Mark, Christie M. Ballantyne, Rafael Beyar, Balram Bhargava, Chris Buller, Antônio Carlos Carvalho, Rafael Díaz, Rolf Doerr, Vladimír Džavík, Shaun G. Goodman, Gilbert Gosselin, Rory Hachamovitch, Christian W. Hamm, Claes Held, Malte Helm, Kurt Huber, Lixin Jiang, Mátyás Keltai, Shun Kohsaka, Iréne Lang, Renato D. Lópes, José López‐Sendón, Aldo P. Maggioni, John Mancini, C. Noel Bairey Merz, James K. 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Bibliographic record
VenueJournal of the American College of Cardiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersDaiichi Sankyo EuropeNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteRelypsaCanadian Institutes of Health ResearchEisaiAmgenEuropean Society of CardiologyAstraZenecaAmarin CorporationEsperion TherapeuticsCedars-Sinai Medical CenterAbbott VascularU.S. Department of Health and Human ServicesSt. Jude MedicalNational Institutes of HealthRegeneron PharmaceuticalsEli Lilly and CompanyCSL BehringAmerican RegentSanofiPfizerCleveland ClinicF. Hoffmann-La RocheGenentechPhilips
KeywordsMedicineRevascularizationIschemiaCardiologyInternal medicineMyocardial infarction
Abstract
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.120
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.031
GPT teacher head0.338
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Citations45
Published2023
Admission routes2
Has abstractno