{"id":"W4402352714","doi":"10.1109/ijcnn60899.2024.10650164","title":"Advancing Pandemic Preparedness through a Data-Driven Hybrid Simulation Model","year":2024,"lang":"en","type":"article","venue":"","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Windsor","funders":"","keywords":"Preparedness; Pandemic; Computer science; Data modeling; Emergency management; Coronavirus disease 2019 (COVID-19); Software engineering; Medicine; Political science","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":[0.0007508114,0.0005871578,0.0005743658,0.0003985059,0.0003382376,0.001192068,0.001258948,0.00153711,0.002949966],"category_scores_gemma":[0.002954167,0.000446509,0.0007288348,0.0003584583,0.0006888197,0.0008089939,0.001311033,0.001390743,0.000273889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009431384,"about_ca_system_score_gemma":0.001426897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01987163,"about_ca_topic_score_gemma":0.01223234,"domain_scores_codex":[0.9997041,0.0001271623,0.00001365901,0.00006468043,0.00004330681,0.0000470869],"domain_scores_gemma":[0.9986265,0.0009707439,0.0001206399,0.00004467079,0.0001331956,0.0001043685],"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":[0.00001811877,0.000009620147,0.0005687845,0.000007677138,0.000009028332,0.00002000453,0.00001450684,0.9948102,0.0001006366,0.003313958,0.0001693478,0.0009581184],"study_design_scores_gemma":[0.000005230193,0.000005631309,0.00005782089,0.000002037882,0.000002809489,0.000002536221,0.000004387232,0.9982917,0.00002533457,0.001438105,0.0001621104,0.000002377419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2106369,0.0005690632,0.7592889,0.003955355,0.0002549737,0.0001709965,0.00201102,0.0007013358,0.02241147],"genre_scores_gemma":[0.9587147,0.0002609675,0.03391815,0.0002800702,0.00005696981,0.0002450134,0.0005754614,0.00004477253,0.005903918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01987163,"threshold_uncertainty_score":0.03951192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4336539599082434,"score_gpt":0.5052185056741257,"score_spread":0.07156454576588234,"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."}}