{"id":"W1974230338","doi":"10.1109/ccece.2013.6567775","title":"Virtual cardiologist &amp;#x2014; A conversational system for medical diagnosis","year":2013,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Conversation; Computer science; Focus (optics); Meaning (existential); Process (computing); Medical diagnosis; Ask price; Human–computer interaction; Multimedia; Psychology; Programming language; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002121372,0.0004705202,0.0003207848,0.0006050931,0.000810185,0.001067997,0.001059256,0.000983062,0.01381236],"category_scores_gemma":[0.006081363,0.0003156204,0.0003201038,0.0002721064,0.0002643258,0.001305904,0.00159478,0.0008516273,0.00403004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000500116,"about_ca_system_score_gemma":0.0009794091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002858061,"about_ca_topic_score_gemma":0.002347087,"domain_scores_codex":[0.9989403,0.0006213643,0.00004647346,0.0001994394,0.0001306913,0.0000618609],"domain_scores_gemma":[0.9976513,0.001599138,0.00008000481,0.0001947057,0.0001879616,0.000286995],"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":[0.002605635,0.0006003805,0.00852738,0.0005922026,0.000169276,0.001466599,0.00629299,0.01549347,0.06171495,0.0192807,0.09874933,0.7845072],"study_design_scores_gemma":[0.0004580047,0.0008648646,0.006418335,0.0001541084,0.0002436338,0.001897694,0.001641017,0.7236632,0.03671557,0.02667483,0.2010273,0.00024145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0772756,0.0009745646,0.8395783,0.002932766,0.0003250692,0.0004819524,0.002474559,0.05326293,0.02269437],"genre_scores_gemma":[0.6597473,0.0002943109,0.3232784,0.0007820922,0.0002266546,0.0004270001,0.002828064,0.0007760521,0.01164003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01381236,"threshold_uncertainty_score":0.04620695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03184602320474247,"score_gpt":0.2570850538251836,"score_spread":0.2252390306204411,"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."}}