{"id":"W2898829623","doi":"10.1145/3274297","title":"MechanicalHeart","year":2018,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; William Osler Health System; University of Waterloo","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Classifier (UML); Baseline (sea); Active listening; Human heart; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001559012,0.0009719048,0.0007530374,0.0008228688,0.001096228,0.002116402,0.001746991,0.001410283,0.2468054],"category_scores_gemma":[0.006954737,0.0004000488,0.0006464278,0.0006548607,0.0004454266,0.002188937,0.003599535,0.0009286653,0.1582628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004388012,"about_ca_system_score_gemma":0.0008272546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001687762,"about_ca_topic_score_gemma":0.003289302,"domain_scores_codex":[0.9990049,0.0001094994,0.00005642724,0.0002587586,0.00044764,0.0001227539],"domain_scores_gemma":[0.9976674,0.00046489,0.0001060489,0.0006395075,0.0006741832,0.0004479514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009271962,0.0001536475,0.004871415,0.0005387125,0.00005211983,0.0005121193,0.000455405,0.0006533259,0.008674147,0.006196145,0.6426373,0.3343283],"study_design_scores_gemma":[0.0001801603,0.0003044023,0.01421887,0.0001833559,0.00004188096,0.00088609,0.0002719922,0.004575024,0.003856576,0.005734853,0.9696574,0.00008932339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05177663,0.004464932,0.1608293,0.007921044,0.008662971,0.002465399,0.05733334,0.09664747,0.6098991],"genre_scores_gemma":[0.2852703,0.002433961,0.09116206,0.007209161,0.002918398,0.002076715,0.08100851,0.01172457,0.5161963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2468054,"threshold_uncertainty_score":0.8256463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04029947875898483,"score_gpt":0.3288402795906193,"score_spread":0.2885408008316345,"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."}}