{"id":"W4399071957","doi":"10.1016/j.jmaa.2024.128527","title":"Stationary distribution and ergodicity of a stochastic multi-species model with Holling type II response function","year":2024,"lang":"en","type":"article","venue":"Journal of Mathematical Analysis and Applications","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Soochow University; Suzhou University; Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Mathematics; Ergodicity; Functional response; Type (biology); Stationary distribution; Distribution (mathematics); Applied mathematics; Function (biology); Statistical physics; Mathematical analysis; Markov chain; Statistics; Predation; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008350259,0.00008135977,0.0004397565,0.0001253378,0.00009554256,0.000008729164,0.00002787092,0.00007170035,0.00009070346],"category_scores_gemma":[0.0002829216,0.00004703216,0.00009927428,0.0003450157,0.0002807792,0.00005233567,0.00002083401,0.0001660399,0.0000017421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001257962,"about_ca_system_score_gemma":0.0000457776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.661478e-7,"about_ca_topic_score_gemma":6.188417e-7,"domain_scores_codex":[0.9991792,0.00004548986,0.0004520392,0.00011675,0.0001222005,0.00008429647],"domain_scores_gemma":[0.9986891,0.0008108108,0.000123636,0.00008497312,0.0001815967,0.00010994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001405088,0.00060851,0.0002032916,0.0004400678,0.00142943,0.000005019368,0.0002824477,0.004993102,0.001655612,0.9879794,0.00004618266,0.0009518586],"study_design_scores_gemma":[0.0002778836,0.000443528,0.003467074,0.0001412714,0.003104047,0.00008374848,0.0001054585,0.8273932,0.00004038225,0.1648533,0.00003334758,0.00005665357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2490094,0.000248109,0.7495108,0.001076307,0.000003106067,0.00008884251,0.00001274357,0.000006756317,0.00004394817],"genre_scores_gemma":[0.9877055,0.00005949465,0.01194192,0.00004317315,0.0000213342,0.00001146517,0.00001043357,0.000004236206,0.0002024968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.823126,"threshold_uncertainty_score":0.1917916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246072392366477,"score_gpt":0.3069226707664574,"score_spread":0.2744619468427926,"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."}}