{"id":"W3091885244","doi":"10.1016/j.mbs.2020.108484","title":"Four-tier response system and spatial propagation of COVID-19 in China by a network model","year":2020,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Canadian Institutes of Health Research; National Natural Science Foundation of China","keywords":"Social distance; Contingency plan; Mainland China; China; Pandemic; Geographic mobility; Public health; Basic reproduction number; Population; Coronavirus disease 2019 (COVID-19); Business; Contingency; Computer science; Environmental health; Geography; Medicine; Computer security; Disease","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003193191,0.0001840803,0.0006041785,0.00004576927,0.0001420538,0.00002953847,0.0002819214,0.0001009993,0.00002128906],"category_scores_gemma":[0.02318669,0.0001205228,0.00006160691,0.0004774296,0.0005162502,0.000082702,0.0002392091,0.0001301674,0.000006130912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100921,"about_ca_system_score_gemma":0.000114207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000601471,"about_ca_topic_score_gemma":0.00001944617,"domain_scores_codex":[0.9976906,0.0004283105,0.000700317,0.0004281698,0.0004184908,0.0003341552],"domain_scores_gemma":[0.9956982,0.003601378,0.0002502544,0.0001687495,0.00002903656,0.0002524424],"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":[0.003361812,0.001250104,0.0299933,0.0171462,0.0001268578,0.00008546696,0.03300716,0.009153092,0.01973156,0.8567625,0.02504612,0.004335829],"study_design_scores_gemma":[0.0004031297,0.0002930754,0.001177667,0.0001544846,0.00002490521,0.000005028569,0.000552135,0.714722,0.0002109134,0.2821307,0.0001102602,0.0002156485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4829427,0.0001149031,0.4983368,0.0172393,0.00002916192,0.0007296656,0.00002502625,0.000128542,0.0004538748],"genre_scores_gemma":[0.9821027,0.000009465036,0.01703019,0.0007435091,0.00002885355,0.00004648355,5.738417e-7,0.00000818218,0.00003003281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7055689,"threshold_uncertainty_score":0.9850414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2025735386244539,"score_gpt":0.3829994410724314,"score_spread":0.1804259024479775,"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."}}