{"id":"W3017817371","doi":"10.1038/s41598-020-63877-w","title":"Algorithmic discovery of dynamic models from infectious disease data","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Computer science; Overfitting; Measles; Rubella; System dynamics; Machine learning; Data mining; Data science; Artificial intelligence; Medicine","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":[0.008766706,0.001311844,0.001712896,0.003812784,0.001060062,0.002482762,0.002276644,0.001609098,0.00144422],"category_scores_gemma":[0.06025251,0.001457942,0.002674565,0.00176464,0.002315777,0.003894774,0.003420377,0.003327975,0.0002699775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777269,"about_ca_system_score_gemma":0.003153204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00353613,"about_ca_topic_score_gemma":0.006054646,"domain_scores_codex":[0.9964497,0.002038601,0.000222536,0.0006238724,0.0005081803,0.000157131],"domain_scores_gemma":[0.9149471,0.07760079,0.002430791,0.003441272,0.001107744,0.0004724019],"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":[0.0001090046,0.000149415,0.013644,0.0003952665,0.0002984567,0.0003170499,0.0004787414,0.8237729,0.0005869548,0.1201904,0.001671538,0.03838625],"study_design_scores_gemma":[0.0000182087,0.00001613621,0.0003675009,0.00001933786,0.00001363265,0.00002725164,0.00004153283,0.8954442,0.0001668179,0.1034154,0.0004612498,0.000008758901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05733599,0.0004107377,0.9379085,0.001792962,0.00003118064,0.000143337,0.0006317814,0.0005232101,0.001222229],"genre_scores_gemma":[0.5511317,0.0007610742,0.4422587,0.0005015892,0.0001697718,0.0005996659,0.003302483,0.0001210118,0.001154083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008766706,"threshold_uncertainty_score":0.04636335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1021660154934955,"score_gpt":0.36350166372655,"score_spread":0.2613356482330544,"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."}}