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Record W2037970011 · doi:10.1093/eurheartj/ehr490

Imaging the right heart: the use of integrated multimodality imaging

2012· review· en· W2037970011 on OpenAlexaff
Emanuela R. Valsangiacomo Buechel, Luc Mertens

Bibliographic record

VenueEuropean Heart Journal · 2012
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineMagnetic resonance imagingCardiac imagingRadiologyCardiac magnetic resonance imagingCardiac magnetic resonanceModalitiesCardiac PETCardiologyPositron emission tomography

Abstract

fetched live from OpenAlex

During recent years, right ventricular (RV) structure and function have been found to be an important determinant of outcome in different cardiovascular and also pulmonary diseases. Currently, echocardiography and cardiac magnetic resonance (CMR) imaging are the two imaging modalities most commonly used to visualize the RV. Most structural abnormalities of the RV can be reliably described by echocardiography but due its complex geometrical shape, echocardiographic assessment of RV function is more challenging. Newer promising echocardiographic techniques are emerging but lack of validation and limited normal reference data influence their routine clinical application. Cardiac magnetic resonance is generally considered the clinical reference technique due to its unlimited imaging planes, superior image resolution, and three-dimensional volumetric rendering. The accuracy and reliability of CMR measurements make it the ideal tool for serial examinations of RV function. Multidetector computed tomography (MDCT) plays an important role in the diagnosis of pulmonary emboli but can also be used for assessing RV ischaemic disease or as an alternative for CMR if contra-indicated. Radionuclide techniques have become more obsolete in the current era. The different imaging modalities should be considered complimentary and each plays a role for different indications.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.194
GPT teacher head0.392
Teacher spread0.197 · 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
GenreReview

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

Citations181
Published2012
Admission routes1
Has abstractyes

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