{"id":"W3138653524","doi":"10.1016/j.tranpol.2021.03.005","title":"On the degree of synchronization between air transport connectivity and COVID-19 cases at worldwide level","year":2021,"lang":"en","type":"article","venue":"Transport Policy","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Coronavirus disease 2019 (COVID-19); Synchronization (alternating current); Pandemic; Degree (music); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Complex network; Computer science; Control (management); Air transport; Computer security; Business; Operations research; Geography; Transport engineering; Engineering; Telecommunications; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007914155,0.0002762753,0.000701626,0.00008412449,0.0003038444,0.000003311232,0.0001720712,0.0001346952,0.0003135467],"category_scores_gemma":[0.005518606,0.0001922459,0.0001839625,0.0004759575,0.0003738255,0.00005348547,0.00003646341,0.0001961061,0.000005974312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002963573,"about_ca_system_score_gemma":0.0003650229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002742349,"about_ca_topic_score_gemma":0.007918385,"domain_scores_codex":[0.9981307,0.0002103767,0.0005856104,0.0004329433,0.0002858258,0.0003545301],"domain_scores_gemma":[0.9892168,0.009847026,0.0002065921,0.0004460725,0.00009105125,0.0001924758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00014914,0.0002613009,0.7775647,0.0009673777,0.0003313093,0.0001965379,0.002448538,0.0003491026,0.0001994636,0.2134527,0.001989394,0.002090435],"study_design_scores_gemma":[0.0007498296,0.0001203169,0.9164978,0.00008734561,0.0002481849,0.00002390558,0.0001321746,0.00002369051,0.001451906,0.07647186,0.003886911,0.0003061125],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495419,0.000185412,0.02489198,0.02264457,0.00002283105,0.0004273636,0.0006138863,0.0001147692,0.001557345],"genre_scores_gemma":[0.9950159,0.0001324015,0.0003972299,0.003439263,0.0001104016,0.00003394155,0.00005058643,0.00002724516,0.0007930369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1389331,"threshold_uncertainty_score":0.7839559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4228166388582371,"score_gpt":0.4239679171730313,"score_spread":0.001151278314794224,"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."}}