{"id":"W4388483046","doi":"10.2196/50869","title":"Patients, Doctors, and Chatbots","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Affect (linguistics); Advice (programming); Relation (database); Work (physics); Medical advice; Psychology; Medicine; Medical education; Nursing; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01078439,0.0004667499,0.0004276278,0.001412672,0.006694509,0.01063256,0.0008391348,0.0048471,0.01286459],"category_scores_gemma":[0.0284378,0.0004822566,0.0002717708,0.000880017,0.01043929,0.009276388,0.006801892,0.004242788,0.001825197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002071251,"about_ca_system_score_gemma":0.002114671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002519033,"about_ca_topic_score_gemma":0.002986623,"domain_scores_codex":[0.9850781,0.0119987,0.0003454523,0.0006078907,0.001289173,0.0006806167],"domain_scores_gemma":[0.9632999,0.02587911,0.003100856,0.0009244965,0.001238583,0.005556986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008648997,0.0004799845,0.03287886,0.00187601,0.0001307968,0.00149451,0.3158496,0.00104603,0.003664058,0.3367493,0.1230143,0.1819516],"study_design_scores_gemma":[0.00018702,0.0007636186,0.01892608,0.002306713,0.0001164254,0.002642229,0.2212006,0.004030591,0.002086581,0.1491744,0.598283,0.0002827982],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.264429,0.02917709,0.04304945,0.3901142,0.006094967,0.00030552,0.0004871405,0.001413514,0.2649291],"genre_scores_gemma":[0.9472145,0.002705778,0.004654131,0.01980241,0.001081798,0.0001333607,0.00008690502,0.0001183163,0.0242029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01286459,"threshold_uncertainty_score":0.05703396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06926865245090238,"score_gpt":0.4579933595618939,"score_spread":0.3887247071109915,"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."}}