{"id":"W4367840102","doi":"10.32920/22749383.v1","title":"COVID-19 Media Impact Map for Canada","year":2023,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Geography; Cartography; Medicine; Virology; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005551777,0.001161838,0.0005869933,0.01074118,0.002984975,0.005339646,0.001153636,0.0006699766,0.1083207],"category_scores_gemma":[0.004232578,0.000429548,0.0008530815,0.02243258,0.0005652013,0.001467976,0.001481832,0.001352604,0.02611186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03494773,"about_ca_system_score_gemma":0.07702346,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9898192,"about_ca_topic_score_gemma":0.9898032,"domain_scores_codex":[0.9985381,0.00004069278,0.00004477871,0.0001048466,0.000913954,0.0003576552],"domain_scores_gemma":[0.9933964,0.0002105829,0.0001745264,0.000144825,0.005499182,0.0005744554],"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":[0.00003782368,0.00001492728,0.002352506,0.0003145713,0.00001697578,0.00006895239,0.0001559911,0.001004933,0.00008691539,0.008170748,0.9680508,0.0197247],"study_design_scores_gemma":[0.00001675471,0.000006566284,0.019401,0.0002901315,0.00001429047,0.00003464628,0.0004383959,0.0006034579,0.0001479595,0.0009811636,0.9780253,0.00004043059],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002062078,0.001313464,0.0008317707,0.001523092,0.0003604012,0.000170073,0.8046902,0.001031147,0.1880178],"genre_scores_gemma":[0.03599868,0.006268086,0.006698679,0.0007678292,0.0001799626,0.00044102,0.7258208,0.001339555,0.2224854],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1083207,"threshold_uncertainty_score":0.3623687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.130417657062857,"score_gpt":0.3234875266294603,"score_spread":0.1930698695666033,"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."}}