{"id":"W4283168167","doi":"10.4018/978-1-6684-5279-0.ch010","title":"Healthcare Informatics During the COVID-19 Pandemic","year":2022,"lang":"en","type":"book-chapter","venue":"Advances in logistics, operations, and management science book series","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Informatics; Pandemic; Telemedicine; Health informatics; Healthcare delivery; Coronavirus disease 2019 (COVID-19); Medicine; Business; Political science; Infectious disease (medical specialty); Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005002407,0.0006412492,0.000339967,0.001213802,0.001550816,0.004181817,0.0005543521,0.001732351,0.02676224],"category_scores_gemma":[0.001075029,0.0003147601,0.0003471751,0.001349504,0.001258792,0.004363008,0.002047558,0.003285178,0.01240939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00230138,"about_ca_system_score_gemma":0.002561358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002762634,"about_ca_topic_score_gemma":0.005856356,"domain_scores_codex":[0.9996246,0.00006414635,0.00001269271,0.00004943962,0.0002142864,0.00003475126],"domain_scores_gemma":[0.999589,0.0001957654,0.00001773112,0.00002322203,0.0001075968,0.00006669246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001142726,0.00003156485,0.0001298506,0.0002229214,0.000003801507,0.0001414558,0.001189704,0.0005038648,0.0005026134,0.1303181,0.6915874,0.1753573],"study_design_scores_gemma":[0.000001218711,0.000005584586,0.0001209111,0.0001999535,0.00000125287,0.0001452403,0.0001599982,0.0001826926,0.0001010736,0.01047496,0.988603,0.000003978002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.001195847,0.05252676,0.01026962,0.02327687,0.009594408,0.0001005045,0.0002711977,0.000535849,0.902229],"genre_scores_gemma":[0.009585794,0.04253561,0.01079837,0.009045366,0.003362451,0.00006658792,0.0003957266,0.0002457207,0.9239645],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02676224,"threshold_uncertainty_score":0.08952862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04601339488059169,"score_gpt":0.348542307451164,"score_spread":0.3025289125705724,"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."}}