{"id":"W2209322152","doi":"10.1016/j.cmpb.2015.10.015","title":"Detecting left ventricular impaired relaxation in cardiac MRI using moving mesh correspondences","year":2015,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; St Joseph's Health Care; Sunnybrook Health Science Centre; London Health Sciences Centre; Université du Québec à Montréal; University of Alberta; Canadian VIGOUR Centre; École de Technologie Supérieure","funders":"","keywords":"Cardiac cycle; Medicine; Doppler imaging; Diastole; Cardiology; Magnetic resonance imaging; Doppler effect; Internal medicine; Nuclear medicine; Radiology; Physics; Blood pressure","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":[0.004149313,0.0001877427,0.0005929004,0.0004872413,0.0000447376,0.00004775548,0.00006520522,0.0001203127,0.000001659802],"category_scores_gemma":[0.0007067556,0.0001561478,0.00007985283,0.0007793651,0.0001349124,0.00009165875,0.0001052344,0.0002829122,8.45048e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001347834,"about_ca_system_score_gemma":0.0001095282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003820089,"about_ca_topic_score_gemma":0.000005357002,"domain_scores_codex":[0.9980616,0.0005062678,0.0004409905,0.0003661808,0.0002846638,0.0003403244],"domain_scores_gemma":[0.9988095,0.0005027336,0.0001229558,0.0002218699,0.0001169366,0.000226053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000672079,0.00006465151,0.4420716,0.00008274303,0.00002525885,0.0002328891,0.00146862,0.0000594683,0.0004859992,0.000007328057,0.00005408272,0.5553801],"study_design_scores_gemma":[0.01122539,0.002616483,0.3740579,0.005209031,0.0005650157,0.001786999,0.004431171,0.5818904,0.002207335,0.001474792,0.01352356,0.001011883],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7673785,0.0114208,0.2183723,0.0004256329,0.001651148,0.000610237,0.000001072423,0.000084754,0.00005552119],"genre_scores_gemma":[0.4565952,0.0001229882,0.5424919,0.0001558427,0.000568261,0.00001137503,0.00002236425,0.00002064184,0.00001149699],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.581831,"threshold_uncertainty_score":0.6367524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07163349726347722,"score_gpt":0.3788344466837872,"score_spread":0.30720094942031,"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."}}