{"id":"W4380264173","doi":"10.3390/v15061352","title":"Novel Approach for Identification of Basic and Effective Reproduction Numbers Illustrated with COVID-19","year":2023,"lang":"en","type":"article","venue":"Viruses","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"Concordia University; Concordia University of Edmonton","keywords":"Coronavirus disease 2019 (COVID-19); Identification (biology); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Basic reproduction number; Epidemic model; Reproduction; 2019-20 coronavirus outbreak; Ordinary differential equation; Statistics; Ordinary least squares; Infectious disease (medical specialty); Mathematics; Computer science; Applied mathematics; Econometrics; Mathematical optimization; Biology; Differential equation; Demography; Medicine; Virology; Outbreak; Ecology; Disease","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":[0.0008720791,0.000546106,0.0005333752,0.001249396,0.0004179139,0.0004550967,0.00082703,0.0006092936,0.001057536],"category_scores_gemma":[0.003911917,0.0002946704,0.0005848909,0.0003985551,0.0005732409,0.0007065557,0.0009066085,0.000989732,0.0003558115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003129483,"about_ca_system_score_gemma":0.0006776665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001370814,"about_ca_topic_score_gemma":0.001118624,"domain_scores_codex":[0.9996403,0.0001165557,0.0000186459,0.00006758887,0.0001338435,0.00002311817],"domain_scores_gemma":[0.9992067,0.0004418416,0.0001097161,0.00007849506,0.0001362225,0.000026987],"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":[0.0001116644,0.0001289445,0.00474988,0.0002918125,0.00007431021,0.0003734915,0.0005125488,0.6268108,0.06648949,0.1294952,0.001587833,0.1693739],"study_design_scores_gemma":[0.000004932097,0.00002582253,0.0003004603,0.000007017789,0.000005031321,0.000116643,0.00001603584,0.9860781,0.003132045,0.008279812,0.002021016,0.00001291579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006200345,0.00006163589,0.9926412,0.00003281944,0.00001785211,0.00001812933,0.00001550387,0.0001035908,0.0009089604],"genre_scores_gemma":[0.1579209,0.0002062559,0.8395523,0.00003536142,0.00004125826,0.0001353897,0.00009371385,0.00006297305,0.001951905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001370814,"threshold_uncertainty_score":0.004612029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3188276028245287,"score_gpt":0.436816814554198,"score_spread":0.1179892117296693,"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."}}