{"id":"W4411507563","doi":"10.1016/j.mbs.2025.109480","title":"Recurrent patterns of disease spread post the acute phase of a pandemic: Insights from a coupled system of a differential equation for disease transmission and a delayed algebraic equation for behavioral adaptation","year":2025,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pandemic; Disease; Structural equation modeling; Adaptation (eye); Phase (matter); Differential equation; Algebraic number; Transmission (telecommunications); Medicine; Computer science; Mathematics; Psychology; Mathematical analysis; Coronavirus disease 2019 (COVID-19); Physics; Neuroscience; Statistics; Pathology; Infectious disease (medical specialty); Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005140803,0.0001786947,0.0005470515,0.00009256048,0.0001462954,0.00001943092,0.0002190953,0.00006355358,0.000006833774],"category_scores_gemma":[0.002263522,0.0000997896,0.0002003428,0.0001819229,0.0002357066,0.00009180978,0.00006543598,0.00004738693,1.313314e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004219016,"about_ca_system_score_gemma":0.00009781829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000703912,"about_ca_topic_score_gemma":0.00002314815,"domain_scores_codex":[0.9981049,0.0001462992,0.0009073952,0.0003217128,0.0003529324,0.000166708],"domain_scores_gemma":[0.9931627,0.005770122,0.0005262674,0.0002078638,0.0002291916,0.0001038406],"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":[0.01587053,0.00975791,0.003928017,0.02209166,0.0007843268,0.000002470031,0.02003968,0.00009635054,0.1106329,0.7506857,0.00004761217,0.06606284],"study_design_scores_gemma":[0.0019905,0.000826935,0.002787535,0.001245828,0.001345252,1.032125e-7,0.00130028,0.6750652,0.001488041,0.3138042,0.000002918226,0.0001432697],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5087711,0.0001099592,0.4892711,0.0002727274,0.00003523927,0.001119367,0.000404381,0.00001540483,7.571717e-7],"genre_scores_gemma":[0.9934851,0.00002573872,0.006009319,0.00002006254,0.00001361203,0.000370009,0.00006495957,0.000006408651,0.000004806288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6749688,"threshold_uncertainty_score":0.4069302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2241884560277963,"score_gpt":0.4285040223944604,"score_spread":0.2043155663666641,"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."}}