{"id":"W4317936738","doi":"10.1007/s00285-023-01873-0","title":"Optimal control by deep learning techniques and its applications on epidemic models","year":2023,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Postdoctoral Research Foundation of China; China Postdoctoral Science Foundation; National Natural Science Foundation of China; Canada Research Chairs; China Scholarship Council; York University","keywords":"Optimal control; Artificial neural network; Computer science; Sensitivity (control systems); Control (management); Artificial intelligence; Deep learning; Mathematical optimization; Mathematics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002742453,0.00007414711,0.0002169639,0.00005286628,0.00005618991,0.000008907084,0.00007286913,0.00005198843,0.00009244091],"category_scores_gemma":[0.0000159027,0.00005228447,0.00006358096,0.00006463949,0.00003400993,0.0000454085,0.00001698729,0.0002711022,0.00002835451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005581205,"about_ca_system_score_gemma":0.000006167886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.295654e-7,"about_ca_topic_score_gemma":5.167825e-9,"domain_scores_codex":[0.9993883,0.00006729752,0.000278501,0.00008365927,0.00004999748,0.0001322376],"domain_scores_gemma":[0.9993302,0.0003457521,0.0001608863,0.00004580235,0.0000424182,0.00007494311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001270846,0.0002635751,0.0002090269,0.00004159991,0.000205584,0.000004314105,0.0001621072,0.01346598,0.021044,0.8222947,0.003633756,0.1385483],"study_design_scores_gemma":[0.0009990139,0.0006449107,0.000007423705,0.00007921109,0.00006977338,0.00008387881,0.0001972628,0.5132207,0.005859751,0.4607385,0.01785366,0.0002459184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1586305,0.0003030559,0.8353896,0.001828405,0.0000461854,0.0002580643,0.000009752092,0.00005567682,0.003478759],"genre_scores_gemma":[0.9979634,0.00009545732,0.001397329,0.00005105484,0.0002479487,0.00002326125,0.000003944689,0.000007808098,0.000209782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8393329,"threshold_uncertainty_score":0.2132099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02226026728300481,"score_gpt":0.3003220789923335,"score_spread":0.2780618117093288,"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."}}