{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006394217,0.0007983837,0.0004059236,0.002822769,0.0008459029,0.001704665,0.0008514407,0.0004761583,0.01158757],"category_scores_gemma":[0.002432154,0.0002924011,0.0005740747,0.002079236,0.0003933147,0.0007542468,0.001281558,0.0006691633,0.002145599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003188469,"about_ca_system_score_gemma":0.006072095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6149016,"about_ca_topic_score_gemma":0.7665788,"domain_scores_codex":[0.9996495,0.00004342695,0.00001885687,0.0000610902,0.000149985,0.0000771256],"domain_scores_gemma":[0.9974765,0.0007412696,0.0001240328,0.0001887009,0.0008616839,0.0006077047],"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":[0.001982258,0.0005753312,0.07607013,0.001039492,0.0003009753,0.002489888,0.004111697,0.02682468,0.01701093,0.003984897,0.6340149,0.2315947],"study_design_scores_gemma":[0.000703964,0.000351184,0.2170454,0.0006826477,0.0002499711,0.0008740891,0.004498921,0.3603401,0.01513531,0.008137472,0.3911803,0.0008006739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"software","genre_scores_codex":[0.3222447,0.001756298,0.09111476,0.006433573,0.0008550216,0.001868395,0.2893597,0.2158516,0.07051591],"genre_scores_gemma":[0.6408954,0.001733614,0.2170122,0.001034861,0.0003010275,0.0007169255,0.1045678,0.006097058,0.02764098],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.3850984,"threshold_uncertainty_score":0.7747326,"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."}}