{"id":"W3198014921","doi":"","title":"Telecommunications networks and public health responses during the COVID-19 pandemic: Evidence from a large national network operator in Canada","year":2021,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Telemedicine; Per capita; Public health; Unemployment; Telecommunications; Population; Coronavirus disease 2019 (COVID-19); Business; Demographic economics; Health care; Economic growth; Economics; Medicine; Engineering; Environmental health","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":[0.001863713,0.0003342859,0.0003550265,0.001921737,0.005581698,0.003106854,0.001473008,0.001018978,0.001988415],"category_scores_gemma":[0.01015718,0.0003530276,0.0006417563,0.005431076,0.002138394,0.001055168,0.002118997,0.002096212,0.0001760026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05455004,"about_ca_system_score_gemma":0.1113932,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9972589,"about_ca_topic_score_gemma":0.9984909,"domain_scores_codex":[0.9971361,0.0003753365,0.0001302631,0.0002230002,0.0009791089,0.001156182],"domain_scores_gemma":[0.9839807,0.002516949,0.003053181,0.0004483567,0.00649671,0.003503968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001613748,0.0001523153,0.9558142,0.0002168232,0.0001274602,0.0004042606,0.01131545,0.0004947843,0.000134512,0.001353942,0.008869759,0.02095502],"study_design_scores_gemma":[0.00002855101,0.00006118957,0.9550119,0.0004204353,0.0001194829,0.00009318592,0.03454128,0.0007810112,0.0001036845,0.0001742997,0.008609881,0.00005502386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689697,0.002629797,0.000226266,0.008659601,0.00004702633,0.0001200014,0.003802984,0.00001677255,0.01552794],"genre_scores_gemma":[0.9923712,0.003282136,0.0002398316,0.001417042,0.00002492061,0.0000313914,0.001134194,0.00001174316,0.001487498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05455004,"threshold_uncertainty_score":0.3957901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1828777047723365,"score_gpt":0.3327673406100455,"score_spread":0.149889635837709,"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."}}