{"id":"W3134769242","doi":"10.1016/j.dib.2021.106939","title":"COVID-19 in Europe: Dataset at a sub-national level","year":2021,"lang":"en","type":"article","venue":"Data in Brief","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds De La Recherche Scientifique - FNRS; Fonds National de la Recherche Luxembourg","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Public health; European union; Scale (ratio); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Big data; 2019-20 coronavirus outbreak; Environmental health; Economic growth; Political science; Geography; Business; Medicine; Economics; Computer science; Disease; Data mining; Virology","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":[0.001730088,0.000862914,0.001064305,0.003280381,0.0004692649,0.001681957,0.001698726,0.001961615,0.01468141],"category_scores_gemma":[0.01001003,0.0004499918,0.001151644,0.006844176,0.0002863344,0.001037975,0.00197469,0.001222479,0.01091465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008269988,"about_ca_system_score_gemma":0.001495957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0182287,"about_ca_topic_score_gemma":0.0147045,"domain_scores_codex":[0.99843,0.0003461075,0.0004006797,0.0003691646,0.0002654984,0.0001886364],"domain_scores_gemma":[0.9968874,0.0008975771,0.0006050911,0.000559882,0.0007542052,0.0002959016],"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":[0.0004231411,0.0001140402,0.02754627,0.001658908,0.0002726314,0.0002108419,0.0001315702,0.001748679,0.0004892133,0.002206828,0.9554727,0.009725245],"study_design_scores_gemma":[0.0006038356,0.00008506067,0.111386,0.00112209,0.0001506687,0.0005378728,0.0004880854,0.001862039,0.0009195835,0.002499882,0.8802418,0.0001031502],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002188106,0.0001522458,0.0002276171,0.0001462709,0.00003035771,0.00002804407,0.9964188,0.0001222497,0.0006863421],"genre_scores_gemma":[0.002971971,0.0001031092,0.0006190346,0.00009361518,0.00001493944,0.0001169665,0.9957288,0.00003461536,0.0003170155],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0182287,"threshold_uncertainty_score":0.04911417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6580591507105042,"score_gpt":0.5052965983658505,"score_spread":0.1527625523446537,"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."}}