{"id":"W4310700278","doi":"10.2196/38799","title":"Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mental health; mHealth; Latent Dirichlet allocation; Computer science; Anxiety; Topic model; World Wide Web; Public health; Psychology; Artificial intelligence; Data science; Medicine; Psychiatry; Nursing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002313395,0.0001450374,0.0002658575,0.001111008,0.0003735562,0.00005517936,0.0003551248,0.00004461984,0.001738277],"category_scores_gemma":[0.00000466637,0.0001672658,0.0001640664,0.001697485,0.00003853523,0.0001335786,0.0001513215,0.0003618223,0.00003510537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001233296,"about_ca_system_score_gemma":0.00005665968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002055528,"about_ca_topic_score_gemma":0.007498799,"domain_scores_codex":[0.9979256,0.0001800476,0.0007643848,0.0004320449,0.0002514295,0.0004464564],"domain_scores_gemma":[0.9993342,0.00002637654,0.000138088,0.0003545248,0.00001891972,0.0001279295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006641445,0.006892187,0.4270245,0.0001497087,0.0002938977,0.00001251201,0.09806395,0.005242073,0.0000155741,0.3919667,0.0005037249,0.06976876],"study_design_scores_gemma":[0.001495135,0.002865276,0.4933175,0.00009380514,0.0001089016,0.000008678994,0.4192237,0.01104421,0.0001245234,0.04740283,0.022143,0.002172474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936943,0.0001775934,0.0007677175,0.0008986623,0.0002994051,0.001016093,0.000201444,0.00006088822,0.002883879],"genre_scores_gemma":[0.9975745,6.381031e-7,0.00002603017,0.0001251589,0.00002375989,0.001211633,0.0007103899,0.00001707962,0.0003107912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3445639,"threshold_uncertainty_score":0.9991743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563295769895436,"score_gpt":0.4429590737817027,"score_spread":0.2866294967921592,"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."}}