{"id":"W2137797572","doi":"10.1098/rsif.2006.0112","title":"Simple models for containment of a pandemic","year":2006,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of New Brunswick; University of Victoria; University of British Columbia; University of Manitoba","funders":"","keywords":"Outbreak; Simple (philosophy); Anticipation (artificial intelligence); Computer science; Pandemic; Vaccination; Epidemic model; Stochastic modelling; Reliability (semiconductor); Disease Eradication; Operations research; Coronavirus disease 2019 (COVID-19); Econometrics; Disease; Virology; Mathematics; Statistics; Artificial intelligence; Biology; Medicine; Infectious disease (medical specialty); Environmental health","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":[0.001204484,0.0001182141,0.0004590917,0.000006631579,0.00008695203,0.000007877174,0.0003475735,0.00008036643,0.00001983551],"category_scores_gemma":[0.0008213141,0.00006348896,0.0008135523,0.0000465217,0.00009201763,0.00003387162,0.0001613047,0.0002072728,4.868172e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002524586,"about_ca_system_score_gemma":0.00003435711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000084298,"about_ca_topic_score_gemma":0.00001530797,"domain_scores_codex":[0.9987176,0.00007821481,0.0007017869,0.000087678,0.0002255302,0.0001891708],"domain_scores_gemma":[0.9968611,0.001969685,0.0008064399,0.0001513743,0.0001818239,0.00002957802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002986148,0.0005101646,0.01211211,0.0003790854,0.0008424247,6.778765e-7,0.001951063,0.4848371,0.001944722,0.009692876,0.4869273,0.0005038751],"study_design_scores_gemma":[0.001513896,0.0004404155,0.001454684,0.0001849074,0.0002589309,0.000005760411,0.001145427,0.1424969,0.004666342,0.840571,0.007083362,0.0001783335],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3059635,0.0007118876,0.6908417,0.001858129,0.0001377745,0.0002654456,0.00001799495,0.00001213096,0.0001914717],"genre_scores_gemma":[0.9914642,0.00002242588,0.007494326,0.0003068417,0.0001260983,0.00000557895,1.212761e-7,0.00001011883,0.0005702872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8308781,"threshold_uncertainty_score":0.2589005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1462822567711837,"score_gpt":0.4000428448208934,"score_spread":0.2537605880497097,"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."}}