{"id":"W2903035140","doi":"10.1142/s0218339018500249","title":"EVALUATION OF THE TUBERCULOSIS TRANSMISSION OF DRUG-RESISTANT STRAINS IN MAINLAND CHINA","year":2018,"lang":"en","type":"article","venue":"Journal of Biological Systems","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Shanxi Scholarship Council of China; National Natural Science Foundation of China","keywords":"Mainland China; Basic reproduction number; Transmission (telecommunications); Tuberculosis; China; Disease; Drug resistance; Vaccination; Drug; Medicine; China mainland; Environmental health; Mainland; Biology; Demography; Virology; Microbiology; Population; Geography; Internal medicine; Computer science; Pharmacology; Pathology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00112366,0.0006382455,0.0004397861,0.0008074374,0.000307076,0.0006906004,0.0007884984,0.0007463671,0.0007995687],"category_scores_gemma":[0.002550036,0.0002129795,0.0006606099,0.0004573177,0.0003645617,0.0009431191,0.0005958575,0.0003170554,0.00006477121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002020179,"about_ca_system_score_gemma":0.001589328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03194968,"about_ca_topic_score_gemma":0.01109185,"domain_scores_codex":[0.9996315,0.0001535065,0.0000185061,0.00004356122,0.00006636664,0.00008657055],"domain_scores_gemma":[0.9989837,0.0005428073,0.0002256992,0.00004158089,0.0001279293,0.00007833517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001135583,0.0001274281,0.0501308,0.00007040622,0.00009563791,0.0006053923,0.0001064629,0.9333539,0.002550532,0.005942789,0.0004147331,0.006488321],"study_design_scores_gemma":[0.00001247124,0.00009017297,0.00616444,0.000005758142,0.00002514355,0.00007018942,0.00005531368,0.9921801,0.0003509973,0.0009336953,0.0001028519,0.000008963047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981995,0.0002739712,0.01493966,0.0005014953,0.00001365115,0.00004885613,0.0001616119,0.00003686487,0.002028812],"genre_scores_gemma":[0.9974336,0.000147255,0.001823226,0.00002339863,0.000005010603,0.00002255514,0.00007522025,0.000003127414,0.0004667085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03194968,"threshold_uncertainty_score":0.06352741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05822602491275545,"score_gpt":0.3259679215098196,"score_spread":0.2677418965970641,"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."}}