{"id":"W3047845636","doi":"10.1007/s11071-020-05861-7","title":"The COVID-19 pandemic: model-based evaluation of non-pharmaceutical interventions and prognoses","year":2020,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Context (archaeology); Pandemic; Public health; Herd immunity; Epidemic model; Population; Econometrics; Epidemiology; Mortality rate; Basic reproduction number; Medicine; Disease; Coronavirus disease 2019 (COVID-19); Environmental health; Geography; Economics; Infectious disease (medical specialty)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002425157,0.0001477233,0.0003036323,0.00002442403,0.0001994824,0.00001907592,0.0001973939,0.00009323671,0.00001736313],"category_scores_gemma":[0.02319064,0.00009776924,0.0001640312,0.000161553,0.0002917033,0.00003448032,0.0001773974,0.0002286561,0.00000262098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001826421,"about_ca_system_score_gemma":0.0002106853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001322821,"about_ca_topic_score_gemma":0.0002320487,"domain_scores_codex":[0.9984046,0.0002554714,0.0005173614,0.0002599193,0.0003645543,0.000198066],"domain_scores_gemma":[0.9951755,0.004020511,0.0002040705,0.0001909966,0.0002328305,0.0001761065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0011614,0.002117051,0.5445728,0.007955913,0.001189424,0.00001217387,0.003133441,0.1890382,0.0006887919,0.07128709,0.005620879,0.1732229],"study_design_scores_gemma":[0.0007453283,0.00008992318,0.000476982,0.00002776856,0.0002666788,0.000001154751,0.0001064751,0.9717414,0.000011815,0.02575017,0.0006819695,0.0001003199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2861457,0.0006321181,0.6896241,0.02177797,0.0000650065,0.00127338,0.000144814,0.0001522308,0.0001846051],"genre_scores_gemma":[0.9592571,0.0001743347,0.03769061,0.002636517,0.00006780444,0.0001019628,0.00003216369,0.00002130232,0.00001826136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7827033,"threshold_uncertainty_score":0.9850374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.570551127763833,"score_gpt":0.5626410919620992,"score_spread":0.007910035801733772,"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."}}