{"id":"W3198159315","doi":"10.23977/acss.2021.050105","title":"Research on Deep Neural Network Solution of Ordinary Differential Equations and Its Application","year":2021,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Ordinary differential equation; Computer science; Discretization; Mathematics; Differential equation; Boundary value problem; Solution set; Numerical partial differential equations; Set (abstract data type); Applied mathematics; Algorithm; Mathematical analysis; Artificial intelligence","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":[0.0001960472,0.00009849063,0.0002396426,0.00006946135,0.00007537757,0.00002985017,0.00005744824,0.00005395009,0.000001351546],"category_scores_gemma":[0.000006221244,0.00009440973,0.0000205306,0.0002182817,0.00001959001,0.0001586476,0.00003402393,0.0001305252,0.00000135827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002189733,"about_ca_system_score_gemma":0.000004081349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007759584,"about_ca_topic_score_gemma":0.00002658496,"domain_scores_codex":[0.9989553,0.0001585777,0.0002956038,0.0002053296,0.000177081,0.000208071],"domain_scores_gemma":[0.9993469,0.0003457189,0.000041493,0.0001292783,0.00009277809,0.00004385021],"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":[0.00001313241,0.00001747428,0.0002459183,0.0002048605,0.00001232922,0.000004779324,0.00008292832,0.9561605,0.005509209,0.004905825,0.00001247466,0.03283055],"study_design_scores_gemma":[0.0002856384,0.0000685464,0.0005643452,0.0001333852,0.000003399363,0.000009588606,0.00005371813,0.9978409,0.0001756412,0.0004129098,0.0003613077,0.00009060498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1157025,0.04495743,0.8381652,0.00001623598,0.0006028795,0.0003057464,0.000004901697,0.00003934511,0.0002057206],"genre_scores_gemma":[0.9987856,0.000555798,0.000184152,0.000005010306,0.0003874672,0.00004885686,0.000008898578,0.00001160181,0.00001259697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8830831,"threshold_uncertainty_score":0.3849917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03243831504456443,"score_gpt":0.3020030548514723,"score_spread":0.2695647398069079,"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."}}