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Record W2047901538 · doi:10.1002/nbm.1164

4D cardiac MRI in the mouse

2007· article· en· W2047901538 on OpenAlexaff
Akiva Feintuch, Yonghong Zhu, Jonathan Bishop, Lorinda Davidson, Jun Dazai, Benoit G. Bruneau, R. Mark Henkelman

Bibliographic record

VenueNMR in Biomedicine · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsUniversity of TorontoSickKids FoundationToronto Centre for PhenogenomicsHospital for Sick Children
Fundersnot available
KeywordsPapillary muscleEjection fractionCardiac VentricleCardiac function curveDiastoleMagnetic resonance imagingCardiac imagingCardiac muscleCardiologyMedicineAnatomyInternal medicineRadiologyVentricleHeart failureBlood pressure

Abstract

fetched live from OpenAlex

With the introduction of mouse models for the study of cardiac morphogenesis, there arises a need for new imaging protocols that can capture both morphological and functional information. High-resolution 2D cardiac cine MRI has often been used to quantify left and right ventricular function. In this study we propose a 3D isotropic cardiac cine MRI protocol with a voxel size of 200 microm(3) as a means of studying cardiac multi-chamber morphology and function. A black blood sequence was used to enhance blood myocardium contrast. Manual segmentation of the ventricles was used to measure ventricular volumes at end diastole and end systole. This method is demonstrated on an Irx4-deficient mouse model. We have been able to identify the volumes of both ventricles dynamically and to show differences in ejection fraction in the mutant. We have also identified an abnormality of the papillary muscle in the mutant that had been missed in previous phenotyping with ultrasound and histology.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.323
Teacher spread0.310 · 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 designBench or experimental
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

Citations26
Published2007
Admission routes1
Has abstractyes

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