{"id":"W2565038447","doi":"10.1016/j.epidem.2016.12.001","title":"Defining epidemics in computer simulation models: How do definitions influence conclusions?","year":2016,"lang":"en","type":"article","venue":"Epidemics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Canada; University of Missouri","keywords":"Public health interventions; Cutoff; Computer science; Epidemic model; Public health; Population; Infectious disease (medical specialty); Disease; Data science; Psychological intervention; Econometrics; Operations research; Risk analysis (engineering); Medicine; Environmental health; Pathology; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003245623,0.0003768396,0.0009195014,0.0001792138,0.0002776177,0.00003160209,0.0003948153,0.0003419937,0.00003065483],"category_scores_gemma":[0.05312444,0.0002626053,0.000198842,0.0004179025,0.0002506799,0.0005107392,0.0006175342,0.0004160682,0.00007175656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004546181,"about_ca_system_score_gemma":0.00007290626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006464162,"about_ca_topic_score_gemma":0.00008298398,"domain_scores_codex":[0.9965037,0.0006821544,0.001120523,0.000678039,0.0003006215,0.0007150252],"domain_scores_gemma":[0.9371474,0.06137982,0.0004870051,0.0006024598,0.000215671,0.0001676737],"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":[0.00003088282,0.00009430604,0.1090854,0.00006808877,0.00004140805,0.00001344871,0.0004588149,0.2367092,0.00004904702,0.6390557,0.004939011,0.009454625],"study_design_scores_gemma":[0.0005311974,0.00004368178,0.004796065,0.0003708991,0.00002395384,0.000003651533,0.00003663962,0.2442453,0.000007097311,0.7479621,0.001649743,0.000329624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2018063,0.0005405436,0.7818587,0.01410107,0.0001857381,0.0004633249,0.00007370715,0.0003259545,0.0006446238],"genre_scores_gemma":[0.8943273,0.0006293112,0.1007755,0.003984208,0.0001291869,0.00006964756,0.000007280312,0.00004078323,0.00003685542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.692521,"threshold_uncertainty_score":0.9999826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3454422967654884,"score_gpt":0.4195550114551164,"score_spread":0.07411271468962799,"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."}}