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Record W2047862142 · doi:10.1016/j.carj.2009.02.006

Canadian Association of Radiologists: Consensus Guidelines and Standards for Cardiac CT

2009· article· en· W2047862142 on OpenAlexafffundabout
Carole Dennie, Jonathan Leipsic, Alan Brydie

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie UniversitySt. Paul's HospitalUniversity of British ColumbiaOttawa Hospital
FundersAssociation Canadienne des Radiologistes
KeywordsMedicineCoronary arteriesCoronary angiographyMedical physicsGold standard (test)RadiologyCardiologyArteryMyocardial infarction

Abstract

fetched live from OpenAlex

Invasive coronary angiography remains the gold standard for imaging of the coronary arteries. Because of poor temporal and spatial resolution, noninvasive imaging of the heart using computed tomography (CT) had remained a challenge until the recent past. Since 1999, and the advent of 4-detector electrocardiogram (ECG)-gated CT, there have been rapid technical developments in CT technology and postprocessing tools, thus enabling an accurate noninvasive assessment of cardiac anatomy including the coronary arteries as well as cardiac function. Today, this relatively new technique increasingly is being requested and performed on a routine basis. Although guidelines and standards for the performance of cardiac CT (CCT) have been published by other societies outside of Canada [1e5], the Canadian Association of Radiologists recognizes that Canadian radiologists play a leading and pivotal role in the safe and proper implementation of CCT throughout the country, as well as in the training and continuing medical education of physicians performing and interpreting CCT studies. This comprehensive article reviews the current evidence for CCT to date and outlines the standards for the implementation of a CCT program. Based on the review of the current literature and on

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)0.005
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.307
Teacher spread0.287 · 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

Citations16
Published2009
Admission routes3
Has abstractyes

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