{"id":"W4313427000","doi":"10.21203/rs.3.rs-2426208/v1","title":"Investigating air travel network changes in Canada, USA and Europe during COVID-19 using open source data","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Open source; Geography; Air travel; Meteorology; Regional science; Computer science; Engineering; Virology; Aviation; Outbreak; Aerospace engineering; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008067549,0.0003715053,0.000288169,0.004584066,0.0006705971,0.001954654,0.000587913,0.0004783408,0.001664644],"category_scores_gemma":[0.006506353,0.0001399293,0.0003883376,0.009868853,0.0004278178,0.000895858,0.001234554,0.0007663746,0.0004384003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00471526,"about_ca_system_score_gemma":0.006183829,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9170843,"about_ca_topic_score_gemma":0.9234499,"domain_scores_codex":[0.9991457,0.00008259023,0.00003771568,0.0001444354,0.000347966,0.0002415587],"domain_scores_gemma":[0.9958767,0.0007701109,0.0009945274,0.0002107645,0.001724115,0.0004238144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002182734,0.0001052511,0.9069483,0.0002401264,0.0003372596,0.00032685,0.001287975,0.0196053,0.0005750031,0.004696898,0.04531821,0.02034056],"study_design_scores_gemma":[0.00001147617,0.00001854976,0.9474487,0.0001274469,0.00005177172,0.00005395002,0.002246412,0.01416147,0.0004457644,0.0007115133,0.03468315,0.0000398201],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.750218,0.0007507114,0.001204422,0.001038181,0.00005073402,0.00004652508,0.2400874,0.0001988187,0.006405166],"genre_scores_gemma":[0.7428842,0.0006903855,0.002171655,0.0001389511,0.0000581968,0.00006263566,0.250703,0.0001049622,0.003186089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08291566,"threshold_uncertainty_score":0.1668079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4592712040221556,"score_gpt":0.4081303689599542,"score_spread":0.05114083506220141,"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."}}