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Record W2315162017 · doi:10.1056/nejm-jw.na40947

For Ischemic Cardiomyopathy, Bypass Surgery May Be Better After All

2016· article· en· W2315162017 on OpenAlexaboutno aff
Howard C. Herrmann

Bibliographic record

VenueJournal watch · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyBypass graftingAnginaCoronary artery diseaseInternal medicineArteryIschemic cardiomyopathyEjection fractionCanadian Cardiovascular SocietyStenosisRandomized controlled trialMedical therapySurgeryHeart failureMyocardial infarction

Abstract

fetched live from OpenAlex

In the previously published STICH trial, 1212 patients (median age, 60) with coronary artery disease (CAD) that was amenable to coronary artery bypass grafting (CABG) and with left-ventricular ejection fractions (LVEFs) ≤35% were randomized to CABG plus medical therapy or medical therapy alone. No participants had ≥50% left-main coronary-artery stenosis or Canadian Cardiovascular Society class III–IV angina. During a median follow-up of 56 months, all-cause mortality (the primary outcome) was similar in the two groups, but the rate of death from cardiovascular causes was slightly lower with …

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 distilled prediction

Teacher imitation

Not 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.282
Teacher spread0.261 · 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 teacher head, 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

Citations0
Published2016
Admission routes1
Has abstractyes

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