{"id":"W4229022227","doi":"10.1016/j.mbs.2022.108824","title":"Learning transmission dynamics modelling of COVID-19 using comomodels","year":2022,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Association of Medical Microbiology and Infectious Disease Canada","keywords":"Computer science; Transmission (telecommunications); Field (mathematics); Dynamics (music); Coronavirus disease 2019 (COVID-19); Data science; Management science; Telecommunications; Engineering; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002437447,0.0009047346,0.0008889955,0.0008424433,0.0006274356,0.001977236,0.001636336,0.002200191,0.01364384],"category_scores_gemma":[0.01228933,0.0005158775,0.001762761,0.0006653193,0.0007292653,0.002005886,0.002287858,0.002271128,0.002396106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001285131,"about_ca_system_score_gemma":0.001418309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0135826,"about_ca_topic_score_gemma":0.01501881,"domain_scores_codex":[0.9991853,0.0004673104,0.00004982657,0.0001379048,0.00009914122,0.00006057273],"domain_scores_gemma":[0.9943116,0.004687936,0.0003570293,0.0001960607,0.0002576393,0.0001897346],"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":[0.00006122369,0.00008204003,0.005537029,0.0002631485,0.00006653949,0.000429675,0.0005943844,0.6043303,0.0006105341,0.3517299,0.01235806,0.02393719],"study_design_scores_gemma":[0.00002978815,0.00003241538,0.0005525795,0.00008420581,0.00002698449,0.0001110429,0.00009350514,0.7896243,0.0002705676,0.1880582,0.02108239,0.00003413077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04637449,0.001754197,0.8981776,0.008473226,0.0002885797,0.0002097262,0.003510018,0.001682624,0.03952951],"genre_scores_gemma":[0.5368093,0.004850891,0.4146944,0.002428644,0.0005307781,0.001183625,0.00417561,0.0009710205,0.03435567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01364384,"threshold_uncertainty_score":0.04564315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4317783653687529,"score_gpt":0.4418099225499816,"score_spread":0.01003155718122872,"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."}}