{"id":"W2140478944","doi":"10.1140/epjb/e2006-00136-7","title":"Effects of population mixing on the spread of SIR epidemics","year":2006,"lang":"en","type":"article","venue":"The European Physical Journal B","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Brock University","funders":"","keywords":"Mixing (physics); Homogeneous; Neighbourhood (mathematics); Geography; Population; Range (aeronautics); Epidemic model; Census; Mixing patterns; Distribution (mathematics); Statistical physics; Demography; Mathematics; 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":[0.002200291,0.0001345817,0.0003649274,0.00002100344,0.0001658266,0.000009642657,0.0003552944,0.00001640477,0.00000223067],"category_scores_gemma":[0.005616715,0.00005774902,0.000240673,0.0001277588,0.0001359816,0.00003233194,0.0001313312,0.0003721864,0.00001473044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003377699,"about_ca_system_score_gemma":0.00000400522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000044877,"about_ca_topic_score_gemma":0.000001363343,"domain_scores_codex":[0.9971391,0.001832703,0.0004756461,0.0001063396,0.0002677088,0.0001785011],"domain_scores_gemma":[0.9831442,0.01595902,0.0005730746,0.0002343658,0.0000608819,0.00002846755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003233158,0.00213207,0.006845342,0.0006572491,0.0005040061,0.00007112322,0.002329427,0.006604332,0.1109034,0.7709309,0.05235264,0.04634612],"study_design_scores_gemma":[0.0002592034,0.0001781288,0.118966,0.0002596005,0.0001094566,0.000005871519,0.00003462592,0.0004032181,0.003635454,0.8757984,0.0002455031,0.0001045279],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860217,0.00008625509,0.001095176,0.001656639,0.00007217477,0.0001801572,0.00000197407,0.00002336233,0.01086257],"genre_scores_gemma":[0.9985067,0.00001668969,0.0002472235,0.0002332217,0.0009171843,0.000001049587,4.200205e-7,0.00001934535,0.00005822007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1121207,"threshold_uncertainty_score":0.6724138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054162020174181,"score_gpt":0.3612508239093506,"score_spread":0.2558346218919325,"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."}}