{"id":"W3014482349","doi":"10.1101/2020.03.29.20046904","title":"Global trends in air travel: implications for connectivity and resilience to infectious disease threats","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; BlueDot (Canada); Public Health Ontario; University of Toronto","funders":"Centers for Disease Control and Prevention","keywords":"Geography; Fragility; Air travel; Demography; Environmental health; Infectious disease (medical specialty); Business; Socioeconomics; Disease; Medicine; Aviation; Economics; Engineering","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":[0.001164658,0.000391532,0.0002696696,0.002181321,0.0004532535,0.001451329,0.0003769993,0.0003882787,0.006285224],"category_scores_gemma":[0.005726722,0.0001475498,0.0009342907,0.003742091,0.0006907021,0.002122425,0.001379072,0.001150349,0.0002901833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008405357,"about_ca_system_score_gemma":0.0006068115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02057794,"about_ca_topic_score_gemma":0.01880678,"domain_scores_codex":[0.9994825,0.0001663841,0.00005669517,0.0001274376,0.00005633171,0.0001105704],"domain_scores_gemma":[0.9972219,0.0006745722,0.001135306,0.0001713364,0.0005161004,0.000280838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007416818,0.00003985531,0.9512456,0.0004661994,0.0005810604,0.0001724225,0.001064351,0.004918814,0.0003530539,0.006432708,0.006894628,0.02775704],"study_design_scores_gemma":[0.000005309247,0.00009350854,0.9737011,0.0004173168,0.0001663673,0.0001723509,0.002456302,0.005464199,0.0001764219,0.005552554,0.01175536,0.00003921312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9296203,0.009001289,0.008560396,0.01355797,0.0004745115,0.0001044791,0.0234073,0.000125126,0.01514862],"genre_scores_gemma":[0.9942957,0.001451137,0.001122802,0.0003099942,0.0001533622,0.00004418324,0.00226023,0.00001478291,0.000347803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02057794,"threshold_uncertainty_score":0.04091632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02652017537845301,"score_gpt":0.3396190296880575,"score_spread":0.3130988543096044,"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."}}