{"id":"W2153736494","doi":"10.1002/apj.5500100103","title":"Time Optimal Control of a Binary Distillation Column","year":2002,"lang":"en","type":"article","venue":"Developments in Chemical Engineering and Mineral Processing","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Optimal control; Bang–bang control; Column (typography); Fractionating column; Binary number; Control (management); Dynamic programming; Control theory (sociology); Distillation; Computer science; Batch distillation; Mathematical optimization; Mathematics; Chemistry; Fractional distillation; Chromatography; 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":[0.00005219549,0.000134835,0.0002102658,0.00009157477,0.0000142966,0.00001409202,0.00004922349,0.00007473474,0.000006161093],"category_scores_gemma":[0.00004682024,0.000148786,0.00001380626,0.0001851064,0.00001961822,0.0001588136,0.00001272885,0.00009453655,0.00000198131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006496017,"about_ca_system_score_gemma":0.000004783852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.706956e-7,"about_ca_topic_score_gemma":6.659975e-8,"domain_scores_codex":[0.9992887,0.000003530258,0.0002935954,0.0001323549,0.00009649697,0.0001852682],"domain_scores_gemma":[0.9998167,0.00002754363,0.00003338756,0.00004857592,0.00002678977,0.00004699994],"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":[0.000005451661,0.00001071886,0.0001604713,0.0001805467,0.00001060174,0.000002457686,0.0002115277,0.733541,0.2576727,0.000004644502,0.00001579944,0.008184111],"study_design_scores_gemma":[0.0007127136,0.000005552306,0.0003262489,0.0001780245,0.000004945763,0.000006656384,0.000005368869,0.9958463,0.002587252,0.000001664668,0.000160068,0.0001651948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9331126,0.00142265,0.06445983,0.00001519958,0.00007590676,0.0001894837,0.000004998799,0.0002312144,0.0004881819],"genre_scores_gemma":[0.9789643,0.00001244591,0.02088139,0.000005253484,0.00002687537,0.00001998344,0.000008085985,0.00002577103,0.00005589326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2623053,"threshold_uncertainty_score":0.6067317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004609765640953531,"score_gpt":0.1781823265789568,"score_spread":0.1735725609380033,"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."}}