{"id":"W4413097620","doi":"10.1016/j.ifacol.2025.07.040","title":"Transmission Neural Networks: Approximation and Optimal Control","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Transmission (telecommunications); Computer science; Control (management); Optimal control; Artificial intelligence; Mathematical optimization; Telecommunications; Mathematics","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":[0.001042794,0.0008870816,0.000957975,0.0004374626,0.0003494472,0.001092143,0.0008588749,0.001602399,0.002051841],"category_scores_gemma":[0.004123361,0.0004933919,0.0005626581,0.0007547645,0.0009818826,0.0009478331,0.0009902196,0.002015871,0.000246973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193996,"about_ca_system_score_gemma":0.00092759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01261132,"about_ca_topic_score_gemma":0.005323462,"domain_scores_codex":[0.9996427,0.0001384586,0.00002065674,0.00006975801,0.00008610064,0.00004230654],"domain_scores_gemma":[0.9989428,0.0007612136,0.00009364761,0.00003853309,0.0001417811,0.00002204124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001619934,0.000009429289,0.0001605916,0.00004494757,0.00001399297,0.00001861955,0.00001619158,0.965251,0.0001593322,0.02386443,0.0004355191,0.01000988],"study_design_scores_gemma":[0.000001736744,0.000003755526,0.00001826112,0.000004685003,0.000001622719,0.000002828096,0.000001793598,0.9950341,0.00003849141,0.004684007,0.0002072648,0.000001513745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01121913,0.003032117,0.9760674,0.0007243098,0.0001575917,0.0000405858,0.00007620796,0.0001494959,0.008533267],"genre_scores_gemma":[0.8676859,0.004651523,0.1147778,0.0002429184,0.0002747886,0.0003881235,0.0002299753,0.00007528583,0.0116736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01261132,"threshold_uncertainty_score":0.02507585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005937148302660547,"score_gpt":0.2338074372835885,"score_spread":0.227870288980928,"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."}}