{"id":"W1982667413","doi":"10.1002/cjce.20318","title":"Trajectory planning for grade transitions: A restricted form approach","year":2010,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Benchmark (surveying); Trajectory; Computer science; Trajectory optimization; Mathematical optimization; Transient (computer programming); Scheme (mathematics); Process (computing); Control theory (sociology); Simple (philosophy); Control (management); Optimal control; Optimization problem; Algorithm; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001288044,0.0001161675,0.0001685343,0.0001459965,0.00005483586,0.00003617703,0.0001980749,0.0001008337,0.000002843941],"category_scores_gemma":[0.0001297447,0.00009872951,0.00008827971,0.0001572341,0.00002255494,0.0001373362,0.000001492751,0.0004808058,2.835316e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001188095,"about_ca_system_score_gemma":0.00009598575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003522024,"about_ca_topic_score_gemma":0.00004816107,"domain_scores_codex":[0.9993098,0.000003657304,0.0002764359,0.00005678467,0.00009036642,0.0002629684],"domain_scores_gemma":[0.9994496,0.00008181298,0.00004514277,0.0001087948,0.00006787054,0.0002467817],"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":[0.000004243866,0.000001946519,0.000004603573,0.0000381822,0.00003667213,0.000003686866,0.0003772203,0.811382,0.1873752,0.0004475311,0.0001159847,0.0002127493],"study_design_scores_gemma":[0.0007691095,0.00001841168,0.00005101569,0.00006982109,0.00004847147,0.000277888,0.0000363817,0.9777972,0.0184547,0.0002624061,0.001995785,0.0002188189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2856846,0.0007639229,0.7114842,0.000235275,0.0009533184,0.0004075125,0.00002528835,0.0001249997,0.0003209177],"genre_scores_gemma":[0.982635,6.428298e-7,0.0168956,0.00001306282,0.0003857652,0.00002063504,0.000005750864,0.00003978122,0.000003796459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6969504,"threshold_uncertainty_score":0.4026072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009044883847140082,"score_gpt":0.190099281812538,"score_spread":0.1810543979653979,"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."}}