{"id":"W3189393616","doi":"10.1007/978-3-030-67303-1_1","title":"The Human Factors of AI in Healthcare: Recurrent Issues, Future Challenges and Ways Forward","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in bioengineering","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Context (archaeology); Health care; Computer science; Artificial intelligence; Applications of artificial intelligence; Data science; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002101909,0.0002826885,0.0005056338,0.0002317848,0.0000561159,0.00001289848,0.00008846622,0.0005066976,0.00001311486],"category_scores_gemma":[0.0001233175,0.0002154021,0.0000796328,0.00007397093,0.00006043612,0.00002781479,0.00003823672,0.001132538,9.261128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001881041,"about_ca_system_score_gemma":0.0001156858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003990369,"about_ca_topic_score_gemma":0.003933602,"domain_scores_codex":[0.9986146,0.00001650164,0.0005499599,0.0003255162,0.0002048882,0.0002885194],"domain_scores_gemma":[0.9991394,0.0002393118,0.0001021357,0.0003218864,0.0001065,0.00009073038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005801105,0.00005444858,0.002600807,0.003481303,0.00008652277,0.00003999245,0.008571904,0.0001741897,0.0005325181,0.06601835,0.00006316618,0.9183188],"study_design_scores_gemma":[0.0008035818,0.003884372,0.03278381,0.03280485,0.0004124666,0.000204485,0.003386589,0.002083951,0.05552142,0.2488805,0.6154192,0.003814824],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03737995,0.8627952,0.0009069192,0.09125971,0.004141016,0.001605051,0.0000235531,0.0001030927,0.001785488],"genre_scores_gemma":[0.9125339,0.08530849,0.0002734518,0.0001978387,0.001208908,0.00002137508,0.00009113149,0.00007241096,0.0002925184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.914504,"threshold_uncertainty_score":0.8783845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1017990299175032,"score_gpt":0.3626480754028975,"score_spread":0.2608490454853943,"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."}}