{"id":"W4390943095","doi":"10.2196/47031","title":"Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study","year":2024,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Fraunhofer-Institut für Zelltherapie und Immunologie; University College London","keywords":"Likert scale; Relevance (law); Health technology; Accountability; Scale (ratio); Stakeholder; Health care; Knowledge management; Psychology; Medical education; Computer science; Medicine; Public relations","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007590897,0.0001402642,0.0003460661,0.0005848269,0.00005464395,0.00001759655,0.0001031975,0.00009769734,0.0002215958],"category_scores_gemma":[0.0001771381,0.0001137778,0.00003414245,0.0009400307,0.0001724992,0.00009881226,0.00002905384,0.0003188475,0.000006638221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164179,"about_ca_system_score_gemma":0.00008955557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001385587,"about_ca_topic_score_gemma":0.001733854,"domain_scores_codex":[0.9983801,0.0001290052,0.0007577663,0.0003473689,0.0001890596,0.0001967137],"domain_scores_gemma":[0.9990724,0.000443824,0.00006998023,0.0002522104,0.00006908661,0.00009245901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003838974,0.0007602744,0.5105357,0.0004244659,0.00002224962,0.000009009545,0.08297554,0.000007955528,0.005148313,0.006152253,0.0001029797,0.3938228],"study_design_scores_gemma":[0.00004344363,0.0007406024,0.7780072,0.0004222087,0.00003800116,0.000002722659,0.1833006,0.0006171158,0.01902604,0.01686892,0.0007283503,0.0002047967],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954661,0.0005089429,0.001796048,0.000341508,0.0002592386,0.001306793,0.000002341742,0.00003945714,0.0002795567],"genre_scores_gemma":[0.9990916,0.00003632882,0.0003661188,0.00002235835,0.0001403365,0.0002373814,0.00001544622,0.00001597895,0.00007448586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3936181,"threshold_uncertainty_score":0.4639724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2466579618029961,"score_gpt":0.5526685501173785,"score_spread":0.3060105883143824,"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."}}