{"id":"W4412366519","doi":"10.1093/rap/rkaf083","title":"Adoption and perception of LLM-based chatbots in health care: an exploratory cross-sectional survey of individuals with rheumatic diseases","year":2025,"lang":"en","type":"article","venue":"Rheumatology Advances in Practice","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Arthritis Research Centre of Canada; Research Canada; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Chatbot; Medicine; Health care; Family medicine; Logistic regression; Cross-sectional study; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001257685,0.0001107085,0.0004058717,0.0003933283,0.00006540737,0.000007982504,0.00005963672,0.0001140717,0.00001413317],"category_scores_gemma":[0.002340467,0.0001053351,0.00001569822,0.0005168869,0.0002817278,0.0008916977,0.00001390336,0.0002152185,0.000001148807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001672551,"about_ca_system_score_gemma":0.001034528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002696372,"about_ca_topic_score_gemma":0.003406018,"domain_scores_codex":[0.9977971,0.0007148306,0.000842278,0.0002831442,0.0001852038,0.0001774975],"domain_scores_gemma":[0.9971539,0.001631161,0.0005199744,0.0002033952,0.0004265245,0.00006499438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001194322,0.0005576826,0.9712205,0.00151666,0.00001313922,0.00000117031,0.002785896,0.0008117032,0.000006392067,0.0005053753,0.000002657988,0.02138449],"study_design_scores_gemma":[0.0003745203,0.0006366725,0.9849381,0.0007783349,0.00001258945,0.00002100289,0.01239081,0.0004120917,0.00007772433,0.0002241393,0.00006212831,0.00007190304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901852,0.007496687,0.001130215,0.0004534985,0.000228976,0.0004270881,0.00001731599,0.00001440056,0.00004660896],"genre_scores_gemma":[0.9929079,0.004285739,0.002405824,0.0001930068,0.00000419483,0.0000667756,0.000125952,0.000008111559,0.000002448913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02131259,"threshold_uncertainty_score":0.429544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06042976859709124,"score_gpt":0.4574589660750253,"score_spread":0.3970291974779341,"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."}}