{"id":"W2087102697","doi":"10.1142/s1793524509000790","title":"STRUCTURED INFLUENZA MODEL FOR META-POPULATION","year":2009,"lang":"en","type":"article","venue":"International Journal of Biomathematics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Mitacs","keywords":"Pandemic; Disease; Computer science; Population; Disease control; Control (management); Epidemic disease; Epidemic model; Coronavirus disease 2019 (COVID-19); Operations research; Econometrics; Demography; Medicine; Mathematics; Environmental health; Artificial intelligence; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001733101,0.001137966,0.001892827,0.001592423,0.0007526435,0.001936568,0.003713355,0.003497737,0.01106903],"category_scores_gemma":[0.005044531,0.0007458079,0.003144021,0.001769783,0.001062525,0.002046544,0.001740936,0.002732175,0.00266421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725945,"about_ca_system_score_gemma":0.00160546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008104843,"about_ca_topic_score_gemma":0.005108715,"domain_scores_codex":[0.9991073,0.0004505749,0.00005898162,0.0001625988,0.0001253419,0.00009523986],"domain_scores_gemma":[0.9978119,0.001068013,0.0003936725,0.000217817,0.0003272778,0.0001813398],"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":[0.00004417963,0.00003686752,0.001041225,0.0001002961,0.0001826423,0.000277126,0.00007016231,0.885471,0.0004149238,0.1078536,0.00197202,0.002535905],"study_design_scores_gemma":[0.00005777201,0.00004111957,0.0001964526,0.00001878995,0.00006436328,0.00007944985,0.00002483222,0.9509348,0.00007103544,0.04548246,0.003011367,0.00001752151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04365032,0.002102416,0.9195412,0.003600786,0.000531006,0.0002570637,0.005698814,0.0006557087,0.02396264],"genre_scores_gemma":[0.7256454,0.00362718,0.2147582,0.001714799,0.0006511292,0.002385778,0.005483171,0.0003423462,0.04539196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01106903,"threshold_uncertainty_score":0.03702956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4573122458130124,"score_gpt":0.508126595027267,"score_spread":0.05081434921425454,"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."}}