{"id":"W4379743420","doi":"10.2196/43120","title":"Democratizing the Development of Chatbots to Improve Public Health: Feasibility Study of COVID-19 Misinformation","year":2023,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Al Jalila Foundation; Pfizer","keywords":"Chatbot; Misinformation; Digital health; Outreach; Health care; Internet privacy; Public health; Population; eHealth; mHealth; Resource (disambiguation); Public relations; Computer science; Medicine; Knowledge management; World Wide Web; Nursing; Political science; Computer security; Environmental health","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":[0.0438636,0.0008672382,0.0007054177,0.00191388,0.006725556,0.003088014,0.002938822,0.003071799,0.006847003],"category_scores_gemma":[0.08206197,0.001133224,0.000783067,0.0007792187,0.003086972,0.004593074,0.005732461,0.002834331,0.001377114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00370875,"about_ca_system_score_gemma":0.01012048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005024286,"about_ca_topic_score_gemma":0.01039884,"domain_scores_codex":[0.9766697,0.01729586,0.0008530906,0.001155383,0.001479462,0.00254652],"domain_scores_gemma":[0.8775055,0.09140499,0.004471758,0.005144008,0.01017743,0.01129635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.003606945,0.08831005,0.08547133,0.005956158,0.0001332283,0.007532818,0.5480311,0.002659323,0.01285782,0.007742319,0.008668225,0.2290308],"study_design_scores_gemma":[0.004849255,0.06671341,0.1250141,0.002491815,0.000338962,0.00197521,0.693049,0.02472369,0.01397463,0.006069662,0.06019866,0.0006016063],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822617,0.00006122053,0.004122216,0.001109231,0.00004690111,0.007362814,0.0001180421,0.0001413437,0.004776571],"genre_scores_gemma":[0.9568601,0.0001671783,0.0238843,0.001412801,0.0000530951,0.01458428,0.0001678826,0.00006117726,0.002809198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0438636,"threshold_uncertainty_score":0.2319757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2784185848588253,"score_gpt":0.4588476240809559,"score_spread":0.1804290392221306,"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."}}