{"id":"W4230325966","doi":"10.32920/ryerson.14654631","title":"Simulation models of current density imaging in studying cardiac states","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Current (fluid); Intracardiac injection; Cardiac electrophysiology; Cardiac imaging; Electrophysiology; Correlation; Computational model; Magnetic resonance imaging; Computer science; Physics; Neuroscience; Algorithm; Mathematics; Cardiology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003136894,0.0005584877,0.0004446143,0.0006716189,0.0003198247,0.0007924994,0.0008185309,0.00135174,0.002105367],"category_scores_gemma":[0.001451593,0.0003503938,0.0008793896,0.0004563477,0.0005690926,0.0006775734,0.0005080947,0.0006266211,0.0003786345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006868499,"about_ca_system_score_gemma":0.0006578994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008997343,"about_ca_topic_score_gemma":0.004725623,"domain_scores_codex":[0.9998648,0.00003995877,0.000008802472,0.00002806438,0.00003765399,0.00002064314],"domain_scores_gemma":[0.9995309,0.0002680667,0.00006871725,0.00002870818,0.0000792353,0.0000242955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001419135,0.00001253202,0.0005524274,0.00002021346,0.000008371484,0.00004616593,0.00004249311,0.9921028,0.001011706,0.00436502,0.0001349038,0.001689237],"study_design_scores_gemma":[0.000001591106,0.000003544164,0.00005905126,0.000002559493,0.000002061127,0.0000100862,0.000004179137,0.998716,0.0001590085,0.0008236405,0.0002161565,0.000002051609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1280269,0.001066139,0.8457995,0.0007143831,0.0001024734,0.0001289526,0.0004751412,0.0006181391,0.02306844],"genre_scores_gemma":[0.9413657,0.0009262422,0.0480152,0.0001298683,0.00003798038,0.0002729121,0.0003123161,0.00009654435,0.008843391],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008997343,"threshold_uncertainty_score":0.01788998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373692016478799,"score_gpt":0.2654705994651531,"score_spread":0.2317336793003651,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}