{"id":"W4398171322","doi":"10.52768/epidemiolpublichealth/1036","title":"Bridging Compartmental Models and Network Analysis in Epidemiological Modelling","year":2024,"lang":"en","type":"article","venue":"Epidemiology and Public Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bridging (networking); Computer science; Network analysis; Homogeneous; Data science; Network model; Social network analysis; Rendering (computer graphics); Management science; Artificial intelligence; World Wide Web; Computer security; Mathematics; Engineering; Social media","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006795314,0.001503399,0.001305692,0.00251543,0.0007453255,0.003524909,0.002971007,0.002498109,0.00309236],"category_scores_gemma":[0.02318174,0.000743321,0.001942195,0.002308483,0.002647841,0.005103361,0.00379625,0.003155036,0.0005152504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003038466,"about_ca_system_score_gemma":0.002498485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006879688,"about_ca_topic_score_gemma":0.005915035,"domain_scores_codex":[0.9950898,0.003549565,0.0001993147,0.0003840684,0.0005735309,0.0002037108],"domain_scores_gemma":[0.9735898,0.02250382,0.001456309,0.0009968354,0.001026968,0.0004262152],"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":[0.00003209161,0.00004183552,0.001296077,0.0001955573,0.0001356903,0.0001283459,0.0003300899,0.3206245,0.0003568102,0.6669207,0.001001282,0.008937125],"study_design_scores_gemma":[0.00000816356,0.00003361146,0.0003030012,0.0001032293,0.00004032549,0.00009819426,0.0001519979,0.6655097,0.0002478692,0.3236699,0.009795665,0.00003838605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01006919,0.003945658,0.970979,0.003098171,0.0003037275,0.0000655625,0.000116283,0.00008512169,0.01133718],"genre_scores_gemma":[0.6137789,0.0169571,0.3514642,0.001291303,0.001022921,0.0005187486,0.0003457773,0.0002484439,0.01437266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006879688,"threshold_uncertainty_score":0.03593749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5222754845619278,"score_gpt":0.4884396475196618,"score_spread":0.033835837042266,"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."}}