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Record W2120128467 · doi:10.1007/s12410-011-9068-6

Imaging as an End Point in Ischemia Trials

2011· article· en· W2120128467 on OpenAlexaff
Andrew G. Howarth, Matthias G. Friedrich

Bibliographic record

VenueCurrent Cardiovascular Imaging Reports · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCardiac imagingIschemiaMyocardial ischemiaInterventional radiologyRadiologyCardiac function curveCardiologyNeuroradiologyInternal medicineNeurologyHeart failure

Abstract

fetched live from OpenAlex

Imaging of cardiac function and anatomy has advanced at an exponential rate over the past two decades. Our ability to quantitatively assess the degree of myocardial ischemia and accurately define the vascular anatomy using noninvasive techniques is greater than ever before. Current advances is cardiac imaging are allowing us to more safely assess patients for myocardial ischemia and better understand the prognostic implications of our findings. This review summarizes the current state of knowledge in cardiac imaging for the assessment of cardiac ischemia with a focus on the use of cardiac MRI.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.322
Teacher spread0.274 · 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.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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