{"id":"W2018070137","doi":"10.1049/iet-its.2013.0091","title":"Multi‐model direct generalised predictive control for automatic train operation system","year":2014,"lang":"en","type":"article","venue":"IET Intelligent Transport Systems","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"State Key Laboratory of Rail Traffic Control and Safety","keywords":"Model predictive control; Computer science; Control (management); Automatic control; Control engineering; Automotive engineering; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007196257,0.0004399259,0.0008081815,0.0001602557,0.0001373251,0.0000641095,0.0002431492,0.0002397546,0.000004524255],"category_scores_gemma":[0.00002795359,0.0004245882,0.0002297261,0.0001354027,0.00002738384,0.000298178,0.000002574499,0.0001266166,0.00002438175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929521,"about_ca_system_score_gemma":0.00003371298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003774317,"about_ca_topic_score_gemma":0.00004547422,"domain_scores_codex":[0.9974656,0.0001206199,0.001149728,0.0004510276,0.0003294785,0.0004835573],"domain_scores_gemma":[0.9988985,0.0001383226,0.000157402,0.0004274302,0.0002036805,0.0001746835],"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":[0.00004055469,0.00002963622,0.0001019257,0.001135996,0.0002003138,0.000001484356,0.0007260051,0.9904551,0.005737746,0.001010683,0.00008854458,0.0004720034],"study_design_scores_gemma":[0.001826448,0.00009272683,0.00005518187,0.000351939,0.0001589746,0.000008257997,0.0002232349,0.9950259,0.0009914488,0.000006007507,0.0008391835,0.0004206581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003673704,0.0005045659,0.9870338,0.00001290276,0.001691977,0.004063178,0.000397399,0.001773748,0.00084877],"genre_scores_gemma":[0.9895667,0.00001668825,0.006966619,0.00002153143,0.0003807714,0.002370503,0.0002434241,0.0001553178,0.000278386],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9858931,"threshold_uncertainty_score":0.9998206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291879077284484,"score_gpt":0.2160940219567763,"score_spread":0.2031752311839315,"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."}}