{"id":"W4396832029","doi":"10.1145/3613905.3638176","title":"Designing Conversational Agents to Facilitate Patient-Physician Communication and Clinical Consultation","year":2024,"lang":"en","type":"article","venue":"","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Chatbot; Computer science; Process (computing); Test (biology); Medicine; Medical education; World Wide Web","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":[0.008919381,0.001043106,0.000398252,0.0006232258,0.001515982,0.003173058,0.001947126,0.00205599,0.008139574],"category_scores_gemma":[0.02920465,0.0006970293,0.0006121516,0.0003219024,0.0008780524,0.003284194,0.003200797,0.001554076,0.002634698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000825979,"about_ca_system_score_gemma":0.001948887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007230038,"about_ca_topic_score_gemma":0.000995403,"domain_scores_codex":[0.9923185,0.00594093,0.0003282184,0.000530531,0.0005601823,0.0003215424],"domain_scores_gemma":[0.9708582,0.02382359,0.00136033,0.001061839,0.001366412,0.001529651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004259946,0.007783974,0.02242725,0.005508844,0.0004692005,0.003005377,0.06810963,0.03323954,0.1143103,0.04529642,0.04180305,0.6537864],"study_design_scores_gemma":[0.003182144,0.01131371,0.01523564,0.002204622,0.0008498062,0.00393275,0.02255851,0.4377504,0.09480918,0.05474972,0.352578,0.0008356086],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.196936,0.00065508,0.7668733,0.003223631,0.0004799132,0.004250484,0.0002884695,0.009181589,0.01811155],"genre_scores_gemma":[0.4262329,0.0003344117,0.5600019,0.001021803,0.0001121627,0.003048681,0.0003254948,0.0004002801,0.008522359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008919381,"threshold_uncertainty_score":0.0471707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2273545909188469,"score_gpt":0.488778354922023,"score_spread":0.2614237640031761,"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."}}