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Record W3209648285 · doi:10.5281/zenodo.4506930

Virtual cohort of 1000 synthetic heart meshes from adult human healthy population

2021· dataset· en· W3209648285 on OpenAlexaff
Cristóbal Rodero, Marina Strocchi, M Marciniak, Stefano Longobardi, John Whitaker, Mark O’Neill, Karli Gillette, Christoph M. Augustin, Gernot Plank, Edward J. Vigmond, Pablo Lamata, Steven Niederer

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsSt. Thomas Hospital
FundersEuropean CommissionResearch Councils UKWellcome
KeywordsPolygon meshCohortPopulationComputer scienceMedicineInternal medicineComputer graphics (images)Environmental health

Abstract

fetched live from OpenAlex

<strong>Dataset Description: </strong>We present a database of four-chamber heart models derived from a statistical shape model (SSM) suitable for electro-mechanical (EM) simulations. Our database consists of 1000 four-chamber heart models generated from end-diastolic CT-derived meshes (available in the repository called ("Virtual cohort of adult healthy four-chamber heart meshes from CT images"). These meshes were used for EM simulations. The weights of the SSM are also provided. <strong>Cardiac meshes:</strong> To<strong> </strong>build the SSM, we rigidly aligned the CT cohort and extracted the surfaces, representing them asdeRham currents. The registration between meshes and computation of the average shape was done using a Large Deformation Diffeomorphic Metric Mapping method. The deformation functions depend on a set of uniformly distributed control points in which the shapes are embedded, and on the deformation vectors attached to these points. It is in this spatial field of deformation vectors (one per each control point) where the Principal Component Analysis (PCA) is applied. Case #20 of the CT cohort was not included. More information on the details can be found in Supplement 3 of the reference paper. We created this cohort by modifying the weight of the modes explaining 90%of the variance in shape (corresponding to modes 1 to 9) within 2 standard deviations (SD) of each mode added to the average mesh. The elements of all the meshes are labelled as follows: Left ventricle myocardium Right ventricle myocardium Left atrium myocardium Right atrium myocardium Aorta wall Pulmonary artery wall Mitral valve plane Tricuspid valve plane Aortic valve plane Pulmonary valve plane Left atrium appendage "inlet" Left superior pulmonary vein inlet Left inferior pulmonary vein inlet Right inferior pulmonary vein inlet Right superior pulmonary vein inlet Superior vena cava inlet Inferior vena cava inlet Left atrial appendage border Right inferior pulmonary vein border Left inferior pulmonary vein border Left superior pulmonary vein border Right superior pulmonary vein border Superior vena cava border Inferior vena cava border Each zipped folder contains 25 meshes and the weights of modes used to construct them for each mesh, A VTK file for each mesh (in ASCII) contains an UNSTRUCTURED GRID with the following fields: POINTS, with the coordinates of the points in mm. CELL_TYPES, having all of the points the value 10 since they are tetrahedra. CELLS, with the indices of the vertices of every element. CELL_DATA, corresponding to the meshing tags. In addition, three descriptive files are included: <em>Normalized_explained_variance.csv </em>contains the percentages of variance explained by each of the 18 modes generated from PCA. <em>Mode_standard_deviation.csv</em> contains absolute standard deviations of each of the 18 modes. <em>Eigenvectors.csv </em>contains the directions of maximum shape variability within the shape population.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.023
GPT teacher head0.276
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations4
Published2021
Admission routes1
Has abstractyes

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