{"id":"W3106450090","doi":"10.3389/fcvm.2020.584727","title":"Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy","year":2020,"lang":"en","type":"article","venue":"Frontiers in Cardiovascular Medicine","topic":"Amyloidosis: Diagnosis, Treatment, Outcomes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Alberta; University of Calgary; Circle Cardiovascular Imaging","funders":"","keywords":"Hypertrophic cardiomyopathy; Medicine; Cardiology; Cardiomyopathy; Internal medicine; Heart failure; Receiver operating characteristic; Cardiac magnetic resonance imaging; Magnetic resonance imaging; Radiology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003689802,0.0002061621,0.0005193216,0.00006114629,0.0001091948,0.000009021597,0.0001139976,0.0001303649,0.000001920617],"category_scores_gemma":[0.0002371554,0.0001458604,0.000417448,0.0001805201,0.000173358,0.000008261269,0.00004590421,0.00009924022,9.707153e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003140133,"about_ca_system_score_gemma":0.00004889149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002890291,"about_ca_topic_score_gemma":0.000004352695,"domain_scores_codex":[0.9986494,0.0001776381,0.0003217773,0.0003310567,0.0003122031,0.0002079392],"domain_scores_gemma":[0.9993286,0.00008272419,0.0001185772,0.0003080089,0.00008457434,0.00007748406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003394102,0.0000333946,0.551965,0.0001472529,0.002215947,0.000005787146,0.0001916675,0.411661,0.002918598,0.000009464855,0.002382473,0.02812998],"study_design_scores_gemma":[0.02281808,0.002446299,0.6078216,0.0004464222,0.008624411,0.00009688023,0.0009050058,0.3136792,0.02684818,0.0004213973,0.01453225,0.00136024],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6661608,0.08277171,0.2465109,0.002676723,0.0007303764,0.001089344,0.00003639219,0.0000142465,0.000009519611],"genre_scores_gemma":[0.9918088,0.0005983018,0.005810006,0.0006240433,0.0007745196,0.0001781402,0.0001813227,0.00002415005,7.635217e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.325648,"threshold_uncertainty_score":0.5948013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01478034073941723,"score_gpt":0.2261021602677599,"score_spread":0.2113218195283427,"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."}}