{"id":"W4323348077","doi":"10.18087/cardio.2023.2.n2380","title":"The association between cardiac mr feature tracking strain and myocardial late gadolinium enhancement in patients with hypertrophic cardiomyopathy","year":2023,"lang":"en","type":"article","venue":"Kardiologiia","topic":"Cardiomyopathy and Myosin Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hypertrophic cardiomyopathy; Cardiology; Feature tracking; Internal medicine; Medicine; Strain (injury); Cardiomyopathy; Gadolinium; Feature (linguistics); Tracking (education); Artificial intelligence; Heart failure; Pattern recognition (psychology); Computer science; Psychology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001486619,0.0002645796,0.0008478069,0.0001217482,0.0003065692,0.00005165525,0.00008462436,0.0002171015,8.400967e-7],"category_scores_gemma":[0.0003341228,0.0001693312,0.0002324713,0.0004714023,0.0001136542,0.0000747283,0.0001003398,0.0004536884,0.00002045291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002316236,"about_ca_system_score_gemma":0.0000574739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001679457,"about_ca_topic_score_gemma":0.000005096809,"domain_scores_codex":[0.9978977,0.0002772437,0.0002819083,0.0004332137,0.0005079739,0.0006018954],"domain_scores_gemma":[0.9988887,0.0004056206,0.0001276864,0.0003154,0.000169438,0.00009314128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002400733,0.00001220823,0.9797978,0.00002763966,0.0007925825,0.00002978109,0.000391868,0.00002669497,0.0002959845,0.0000121383,0.001651332,0.01672192],"study_design_scores_gemma":[0.001863809,0.000369956,0.9878497,0.0000719975,0.0004031507,0.000001988067,0.0002698848,0.000003671847,0.00008493458,0.00005208172,0.008828084,0.0002007635],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949821,0.001172864,0.00001563886,0.001170369,0.0005894235,0.0007837215,0.0001356333,0.0001191732,0.001031117],"genre_scores_gemma":[0.9971734,0.001246571,0.00004018836,0.0001018512,0.0007294794,0.00009788937,0.0001689299,0.00002857138,0.0004130653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01652116,"threshold_uncertainty_score":0.6905128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129992545413327,"score_gpt":0.240378441570728,"score_spread":0.2273791870293953,"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."}}