{"id":"W4405077066","doi":"10.1504/ijstl.2024.143138","title":"Disruption risks to global container shipping network in the presence of COVID-19 pandemic: a static structure and dynamic propagation perspective","year":2024,"lang":"en","type":"article","venue":"International Journal of Shipping and Transport Logistics","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Container (type theory); Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; Business; Risk analysis (engineering); Virology; Medicine; Outbreak; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004665457,0.0001047194,0.000158146,0.00009090705,0.00002744807,0.00006014706,0.0001314835,0.00005468586,0.00000867504],"category_scores_gemma":[0.0002035909,0.00007675787,0.00003231947,0.0001331623,0.00008708968,0.00009237892,0.000009195583,0.0002472064,9.182273e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001808826,"about_ca_system_score_gemma":0.00007332404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001818007,"about_ca_topic_score_gemma":0.000488131,"domain_scores_codex":[0.9990919,0.0000330429,0.0003869764,0.0001050865,0.0002667859,0.0001161839],"domain_scores_gemma":[0.9994394,0.0002202844,0.00007695681,0.00004816152,0.0001453723,0.00006988983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001518204,0.00002610137,0.1581929,0.0004135076,0.000223295,0.000532085,0.006469307,0.7908815,0.0001000369,0.03364018,0.00004367082,0.009325571],"study_design_scores_gemma":[0.001194459,0.0003031917,0.4162645,0.001529283,0.0003146775,0.001714326,0.004927165,0.456645,0.000007396708,0.1154482,0.001200429,0.0004513228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3716183,0.001705607,0.624801,0.0008807725,0.0005086761,0.0001557465,0.0001696037,0.00002353668,0.0001367698],"genre_scores_gemma":[0.9980003,0.0004952709,0.001247172,0.00009744192,0.0001325,0.000001951851,0.00001480572,0.000007273398,0.000003286549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.626382,"threshold_uncertainty_score":0.3130095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03802080113844861,"score_gpt":0.3366649506668474,"score_spread":0.2986441495283988,"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."}}