{"id":"W4309938386","doi":"10.1177/15353702221140406","title":"Applied artificial intelligence in healthcare: Listening to the winds of change in a post-COVID-19 world","year":2022,"lang":"en","type":"article","venue":"Experimental Biology and Medicine","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Active listening; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Applications of artificial intelligence; Value (mathematics); Psychology; Artificial intelligence; Engineering ethics; Medicine; Computer science; Engineering; Virology; Pathology","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":[0.0008634952,0.0001071645,0.0002887915,0.0003987681,0.000152845,0.000001577868,0.0001008746,0.00005334354,0.0003461395],"category_scores_gemma":[0.0001796471,0.00007873511,0.00001997845,0.0006877861,0.0002182275,0.00001974535,0.00009533142,0.0003256026,0.000004112857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291243,"about_ca_system_score_gemma":0.0001603069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01603889,"about_ca_topic_score_gemma":0.003751621,"domain_scores_codex":[0.9987031,0.0001372201,0.000504291,0.0002766852,0.0001233632,0.0002553838],"domain_scores_gemma":[0.9993522,0.0001995077,0.00008042521,0.0001642142,0.000024192,0.0001794638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.005694204,0.001022454,0.1137394,0.0001998716,0.00003240939,0.00006692405,0.3239893,0.00005914512,0.1622628,0.06852041,0.0005377909,0.3238754],"study_design_scores_gemma":[0.001203748,0.02089858,0.05373373,0.0005417006,0.00007193385,0.0003868286,0.6268123,0.001356492,0.2389649,0.01571725,0.0393284,0.0009841305],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.859395,0.004090087,0.0000445795,0.1346386,0.0005719683,0.000994244,0.000006095528,0.00001313916,0.0002462779],"genre_scores_gemma":[0.9719546,0.00005926892,0.00007794526,0.02701839,0.0003125302,0.0004874715,0.00005006374,0.000007350895,0.00003235168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3228912,"threshold_uncertainty_score":0.9905134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2418406239941682,"score_gpt":0.4938416727257245,"score_spread":0.2520010487315563,"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."}}