{"id":"W4234737866","doi":"10.15586/jptcp.v27isp1.757","title":"Forecasting of COVID-19 infections in E7 countries and proposing some policies based on the Stringency Index","year":2020,"lang":"en","type":"article","venue":"Journal of Population Therapeutics and Clinical Pharmacology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Index (typography); China; Developing country; Econometrics; 2019-20 coronavirus outbreak; Empirical research; Economics; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Development economics; Economic growth; Geography; Statistics; Mathematics; Computer science; Virology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001899559,0.0001019591,0.0004258579,0.00007456244,0.0001343719,0.00001198006,0.00008357449,0.00009763696,0.00002716689],"category_scores_gemma":[0.005127472,0.0000623856,0.00008672346,0.0001363118,0.0002158345,0.0000571856,0.00005298683,0.0003983222,1.214421e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005099136,"about_ca_system_score_gemma":0.00007311014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004874155,"about_ca_topic_score_gemma":0.00002795554,"domain_scores_codex":[0.9980552,0.0005266338,0.001041144,0.0001131516,0.000136416,0.0001274293],"domain_scores_gemma":[0.9886317,0.01030722,0.0007996858,0.00004619865,0.0001146299,0.0001005219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004529639,0.0002625962,0.9833905,0.0001613305,0.0001707445,0.00000484963,0.0006319884,0.003482908,0.0000919164,0.009248452,0.000364047,0.001737676],"study_design_scores_gemma":[0.006886791,0.00457067,0.349532,0.0001546238,0.0007796561,0.00002088839,0.0007713284,0.3298593,0.0001145399,0.2934758,0.01344459,0.0003897365],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9349366,0.0003328985,0.001832164,0.06246017,0.0001994615,0.0002156845,0.000004692018,0.000007932296,0.00001037325],"genre_scores_gemma":[0.9764373,0.0006409058,0.0002305199,0.02240848,0.0002722211,0.000002435341,3.185588e-7,0.000006550506,0.000001243107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6338585,"threshold_uncertainty_score":0.6138433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4836320208898242,"score_gpt":0.5329091549962555,"score_spread":0.04927713410643131,"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."}}