{"id":"W3049652883","doi":"10.1155/2020/8867316","title":"COVID-19 Outbreak in Colombia: An Analysis of Its Impacts on Transport Systems","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":191,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subsidy; TRIPS architecture; Business; Externality; Government (linguistics); Public transport; Local government; Pandemic; Coronavirus disease 2019 (COVID-19); Transport engineering; Economics; Geography; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009366805,0.0002017166,0.001237274,0.0003459693,0.00004171364,0.000005310453,0.0001978258,0.0001157647,0.00003724825],"category_scores_gemma":[0.002532592,0.0001608263,0.0003526751,0.001083958,0.00004175969,0.0003075692,0.000001834793,0.0002796701,7.616802e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002340967,"about_ca_system_score_gemma":0.0001624677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008349642,"about_ca_topic_score_gemma":0.001146232,"domain_scores_codex":[0.9972023,0.0001626003,0.001687633,0.0002428878,0.0004870064,0.000217615],"domain_scores_gemma":[0.9966341,0.001240429,0.001305956,0.0001385451,0.0002530991,0.00042792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001606729,0.0004225917,0.1278594,0.0008522669,0.0006995331,0.0001818187,0.008823403,0.8532215,0.00320048,0.002853488,0.00006511712,0.0002136575],"study_design_scores_gemma":[0.002422499,0.001667453,0.9869545,0.0001716424,0.001499231,0.000002120768,0.00288161,0.001852732,0.000352499,0.001344092,0.0006078151,0.0002438206],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892567,0.0002962981,0.00826462,0.001594979,0.00009273335,0.0003388798,0.00009993866,0.00002805166,0.00002775988],"genre_scores_gemma":[0.9973939,0.000327412,0.001279612,0.0008932839,0.00004765272,0.000008149848,0.00003032203,0.00001568786,0.000003951222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8590951,"threshold_uncertainty_score":0.6558307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1524409671983659,"score_gpt":0.41825691247346,"score_spread":0.2658159452750941,"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."}}