{"id":"W4400701402","doi":"10.1186/s13662-024-03818-3","title":"A unified stochastic SIR model driven by Lévy noise with time-dependency","year":2024,"lang":"en","type":"article","venue":"Advances in Continuous and Discrete Models","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dependency (UML); Uniqueness; Discontinuity (linguistics); Nonlinear system; Extinction (optical mineralogy); Noise (video); Stochastic modelling; Persistence (discontinuity); Applied mathematics; Statistical physics; Computer science; Unified Model; Mathematics; Statistics; Mathematical analysis; Physics; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001095202,0.0009685913,0.001582881,0.0008841463,0.0003742998,0.001699941,0.002983372,0.001922313,0.002472084],"category_scores_gemma":[0.001713494,0.0005035494,0.001428338,0.000924674,0.001230334,0.001828086,0.001480492,0.001287814,0.0004454014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008076683,"about_ca_system_score_gemma":0.0008969043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003067496,"about_ca_topic_score_gemma":0.002067305,"domain_scores_codex":[0.9992535,0.0002388602,0.00004024747,0.0001677838,0.0001553439,0.0001442494],"domain_scores_gemma":[0.9992309,0.000244585,0.0002330171,0.00004867224,0.0001458488,0.00009705641],"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":[0.00007410474,0.00005854397,0.001443493,0.0001269654,0.0001186412,0.0006984753,0.0001632356,0.571937,0.006122164,0.4110721,0.001664325,0.006520849],"study_design_scores_gemma":[0.00002509004,0.00006168575,0.0002869315,0.000008553822,0.00004218748,0.0001571193,0.00002502659,0.9707097,0.0002084071,0.02750456,0.0009461874,0.0000245176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07721323,0.0009671624,0.9084634,0.001078229,0.0002129806,0.00004778206,0.000314484,0.0002185067,0.01148419],"genre_scores_gemma":[0.9392519,0.001505376,0.03606127,0.0003271822,0.0003106667,0.0001708565,0.0003719416,0.00008606934,0.02191458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003067496,"threshold_uncertainty_score":0.008269906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0106194623166657,"score_gpt":0.2735791016772152,"score_spread":0.2629596393605494,"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."}}