{"id":"W3130702321","doi":"10.1109/bigdatase50710.2020.00010","title":"Big Data Science on COVID-19 Data","year":2020,"lang":"en","type":"article","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Big data; Data science; Coronavirus disease 2019 (COVID-19); Computer science; Disease; Epidemiology; Variety (cybernetics); Data mining; Infectious disease (medical specialty); Medicine; Artificial intelligence; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0008057773,0.0001248415,0.0002003137,0.0001205179,0.0001558129,0.00007537281,0.00224579,0.00003821643,0.0005260555],"category_scores_gemma":[0.01387915,0.0001002192,0.00001567365,0.0009611977,0.0003222066,0.0003471943,0.002612131,0.000181985,0.000696652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485735,"about_ca_system_score_gemma":0.002439081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005252298,"about_ca_topic_score_gemma":0.00006491469,"domain_scores_codex":[0.997652,0.00002412248,0.0001891015,0.001154312,0.0006955985,0.0002848926],"domain_scores_gemma":[0.994482,0.0004439689,0.00004574428,0.00411235,0.00005196128,0.0008640052],"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":[0.00008124077,0.0001782581,0.003010002,0.0001267084,0.00001534424,0.0001197217,0.0001823933,0.00002266897,0.003165701,0.0005439995,0.9803759,0.01217807],"study_design_scores_gemma":[0.000881244,0.0002275235,0.001231374,0.00003763682,0.00005299778,0.00001087726,0.00007092625,0.01617259,0.001227619,0.00001588249,0.9799414,0.0001299326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006594729,0.00009066024,0.004697959,0.9823179,0.00045881,0.0004369596,0.0003385274,0.0004609071,0.004603599],"genre_scores_gemma":[0.342382,0.00005533189,0.001982822,0.654249,0.0006321006,0.000002719684,0.0004436627,0.00001892341,0.0002334803],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3357872,"threshold_uncertainty_score":0.9944274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4690655048335061,"score_gpt":0.4562715510661046,"score_spread":0.0127939537674015,"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."}}