{"id":"W2986109145","doi":"10.1002/rnc.4805","title":"A trajectory‐based method for constructing null controllable regions","year":2019,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Boundary (topology); Affine transformation; Nonlinear system; Mathematics; Trajectory; Null (SQL); Control theory (sociology); Lyapunov function; Optimal control; Set (abstract data type); Construct (python library); Mathematical optimization; Computer science; Control (management); Mathematical analysis; Artificial intelligence","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":[0.0003851363,0.0001346912,0.0003546004,0.0001908607,0.0000296545,0.00005766264,0.0001696304,0.00007291717,0.00002577695],"category_scores_gemma":[0.0001589547,0.000122606,0.000141094,0.00005603607,0.00002500897,0.0002402827,0.000005912523,0.0001484896,0.000002656404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007338952,"about_ca_system_score_gemma":0.00005878742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003054567,"about_ca_topic_score_gemma":0.000005185423,"domain_scores_codex":[0.9989961,0.00004032414,0.0004816628,0.0001068857,0.0002176835,0.0001573428],"domain_scores_gemma":[0.9984403,0.0005274111,0.0002590473,0.00008031901,0.0006192594,0.00007368834],"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":[0.0004555552,0.00001896584,0.0007905699,0.00002829885,0.0003745166,0.000008077067,0.00004839585,0.9804955,0.01300517,0.0004990702,0.0001508918,0.004125036],"study_design_scores_gemma":[0.009972317,0.0001030061,0.00003119005,0.00009182881,0.0000636316,0.0001106809,0.0001229887,0.9811134,0.0005554167,0.0001376872,0.00756763,0.0001301796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01068792,0.0005903814,0.9857682,0.0005012529,0.00162546,0.0003562815,0.00005555797,0.0000415481,0.0003733996],"genre_scores_gemma":[0.6728436,0.00002647379,0.3260449,0.0001917039,0.0007479779,0.00001235807,0.00000775329,0.00003555172,0.00008967829],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6621557,"threshold_uncertainty_score":0.4999729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00916551681233539,"score_gpt":0.2489313220721932,"score_spread":0.2397658052598578,"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."}}