{"id":"W4413567588","doi":"10.64628/aam.54ma9e4x7","title":"Building back better, during and after COVID-19, with faster broadband","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Broadband; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Telecommunications; Computer science; Geography; Virology; Medicine; Outbreak; Internal medicine","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":[0.01193938,0.0008578998,0.0005050063,0.001582747,0.003737625,0.01512669,0.002203033,0.005251862,0.09674581],"category_scores_gemma":[0.04237686,0.0006318788,0.0009088953,0.002107395,0.001212534,0.01119649,0.007740254,0.006850779,0.02222716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004974895,"about_ca_system_score_gemma":0.01940311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02669304,"about_ca_topic_score_gemma":0.0315204,"domain_scores_codex":[0.9869021,0.004457389,0.0004410013,0.001015115,0.002850897,0.004333552],"domain_scores_gemma":[0.9628049,0.005896994,0.002307134,0.003609129,0.007841333,0.01754057],"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":[0.0009534966,0.002327285,0.03156052,0.0009172429,0.0001218601,0.000346651,0.007537767,0.001093684,0.004669154,0.03673059,0.6141217,0.2996201],"study_design_scores_gemma":[0.0004422928,0.0009956063,0.1039392,0.001358373,0.0001324471,0.000290724,0.03061039,0.001742671,0.003808968,0.01547689,0.841009,0.0001933661],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.1931291,0.002445144,0.03093183,0.3793943,0.0141047,0.001451535,0.007617868,0.01010914,0.3608164],"genre_scores_gemma":[0.7008564,0.002372542,0.07140647,0.06090626,0.002912228,0.001204823,0.00966421,0.004006856,0.1466702],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.09674581,"threshold_uncertainty_score":0.323647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04118177410877991,"score_gpt":0.3483646945965644,"score_spread":0.3071829204877844,"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."}}