{"id":"W3045521640","doi":"10.5539/ijsp.v9n5p23","title":"A Real Time and Interactive Web-Based Platform for Visualizing and Analyzing COVID-19 in Canada","year":2020,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Visualization; Computer science; Government (linguistics); Data science; Web application; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Outbreak; World Wide Web; Data mining; Medicine; Virology; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000318546,0.00007745352,0.0002308913,0.00005529777,0.00002265712,0.00003137864,0.0000542506,0.00001715948,0.00002812908],"category_scores_gemma":[0.001760155,0.00006844752,0.00001823047,0.00003992568,0.00005604741,0.0000877085,0.0000361564,0.0001097996,1.05383e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003850077,"about_ca_system_score_gemma":0.00153886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02799462,"about_ca_topic_score_gemma":0.06705941,"domain_scores_codex":[0.9991869,0.00003054936,0.0003525854,0.0001388327,0.000208726,0.00008235903],"domain_scores_gemma":[0.9984902,0.0006993356,0.0002048257,0.0000377998,0.0002867656,0.0002810436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007692266,0.000143772,0.9503661,0.0007262067,0.0003893852,0.0005572109,0.0009113441,0.0003066181,0.001535072,0.00148283,0.003577546,0.03231166],"study_design_scores_gemma":[0.0135433,0.001048552,0.6426579,0.0004059224,0.0001791013,0.000227592,0.0003880182,0.3213145,0.0001496652,0.00906508,0.0106635,0.0003568811],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809966,0.00009428072,0.0122808,0.003640078,0.00006546787,0.0002223371,0.002665323,0.00000487075,0.00003020585],"genre_scores_gemma":[0.9855861,0.00008212695,0.0133518,0.0008364929,0.00005463012,0.000002639886,0.00007757476,0.000005883367,0.000002723262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210079,"threshold_uncertainty_score":0.9784781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02698138869634621,"score_gpt":0.3300981834116271,"score_spread":0.3031167947152809,"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."}}