MétaCan
Menu
Back to cohort
Record W2325178488 · doi:10.5152/dir.2014.14275

Prevalence of dual left anterior descending artery variations in CT angiography

2014· article· en· W2325178488 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDiagnostic and Interventional Radiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCoronary Artery Anomalies
Canadian institutionsCircle Cardiovascular Imaging
Fundersnot available
KeywordsMedicineAngiographyRadiologyDual (grammatical number)Coronary angiographyCardiologyMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE: We aimed to evaluate the frequency and features of dual left anterior descending artery (LAD) variants using computed tomography (CT) angiography. METHODS: A total of 1337 consecutive coronary CT angiography examinations performed between April 2010 and December 2013 were retrospectively evaluated for the presence of dual LAD. CT examinations were performed with either 64- or 320-row multidetector CT scanners. All CT angiography images were evaluated for the presence and morphologic features of dual LAD subtypes. RESULTS: Fifty-six dual LAD variations (4%) were identified in this study population. Type 1 was the most common type of dual LAD (n=48), while Type 3 (n=3) and Type 4 (n=2) were infrequent and Type 2 was not detected. Additionally, we detected previously unclassified dual LAD variations in three cases. CONCLUSION: Dual LAD may be a relatively more common variant than described in the medical literature, which is mostly based on catheter angiography studies. Coronary CT angiography seems markedly efficacious for detecting and documenting the anatomical details of dual LAD subtypes, as well as showing other associated cardiocoronary anomalies.

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.

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)0.000
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 score0.004
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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