{"id":"W2999198340","doi":"10.1101/19012724","title":"Algorithmic discovery of dynamic models from infectious disease data","year":2019,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Virology and Viral Diseases","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Overfitting; Computer science; System dynamics; Measles; Identification (biology); Machine learning; Data science; Data mining; Artificial intelligence; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009665993,0.001166752,0.001736358,0.003697405,0.0009382028,0.002490981,0.002036195,0.001750054,0.00176156],"category_scores_gemma":[0.06513704,0.00134874,0.002265741,0.001575697,0.002742394,0.003513301,0.003428123,0.003271783,0.0002553697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771323,"about_ca_system_score_gemma":0.002379254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003304448,"about_ca_topic_score_gemma":0.004243102,"domain_scores_codex":[0.9962555,0.00232718,0.0001927547,0.0005894008,0.0004697917,0.0001653029],"domain_scores_gemma":[0.8881071,0.1029717,0.002938626,0.00392379,0.001341051,0.0007177196],"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":[0.0001293106,0.0001294309,0.01243583,0.0002814214,0.0002226381,0.0002686094,0.0003411687,0.8620406,0.000429041,0.1025202,0.001675381,0.01952624],"study_design_scores_gemma":[0.00001505375,0.00001090896,0.0002655506,0.00001337587,0.000007695643,0.00001571619,0.00002430872,0.9237809,0.0001147606,0.07549568,0.0002504163,0.00000570594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1062993,0.0004510591,0.8876868,0.002441555,0.00003906613,0.0001452417,0.0007642008,0.0006342084,0.001538459],"genre_scores_gemma":[0.7303313,0.0005171125,0.2634648,0.0005076448,0.0001882551,0.0004286663,0.003039579,0.0001317924,0.001390814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009665993,"threshold_uncertainty_score":0.05111927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0384276974071841,"score_gpt":0.309875438049852,"score_spread":0.2714477406426679,"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."}}