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Record W4391231537 · doi:10.1097/rti.0000000000000773

Approach to Imaging of Patients Presenting With Acute Coronary Syndrome With No Culprit Lesion Identified at Angiography

2024· article· en· W4391231537 on OpenAlex
Tiffany Ni, Wendy Tsang, Elsie T. Nguyen

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

VenueJournal of Thoracic Imaging · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineCulpritRadiologyDifferential diagnosisMagnetic resonance imagingChest painAcute coronary syndromeAngiographyPresentation (obstetrics)Emergency departmentCoronary angiographyMyocardial infarctionCardiologyPathology

Abstract

fetched live from OpenAlex

Chest pain is a common chief complaint among patients presenting to the emergency department. However, in the scenario where the clinical presentation is consistent with acute coronary syndrome and no culprit lesions are identified on angiography, clinicians and cardiac imagers should be informed of the differential diagnosis and appropriate imaging modalities used to investigate the potential causes. This review describes an imaging-based algorithm that highlights the diagnostic possibilities, their differentiating imaging features, and the important role of cardiovascular magnetic resonance imaging for narrowing the differential diagnosis.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.028
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.294
Teacher spread0.283 · 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