{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005476457,0.0005799985,0.0008060947,0.0003374672,0.0008640095,0.001182698,0.0004870999,0.0006631343,0.003891478],"category_scores_gemma":[0.001081403,0.0003856996,0.0002174594,0.0003343723,0.0008983244,0.0004315303,0.0006721632,0.0006478269,0.0003090691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001313499,"about_ca_system_score_gemma":0.001795073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01244043,"about_ca_topic_score_gemma":0.006680528,"domain_scores_codex":[0.9995443,0.00008125624,0.00001607492,0.00009186567,0.0001674185,0.00009902912],"domain_scores_gemma":[0.9994905,0.0002189704,0.0000865358,0.00002213214,0.0001278927,0.00005401048],"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":[0.0008265588,0.0001681646,0.0004430166,0.0002643998,0.00002513673,0.0001137907,0.0001035142,0.8683864,0.07689949,0.01440445,0.001513032,0.0368521],"study_design_scores_gemma":[0.00006833508,0.0001543182,0.0002121691,0.000007715968,0.00001031397,0.000008609336,0.00001171901,0.9793658,0.01687571,0.002218121,0.001048454,0.0000186265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3833161,0.0009717749,0.587265,0.001129187,0.0002826026,0.0002362012,0.0002747387,0.001309188,0.02521526],"genre_scores_gemma":[0.9790205,0.00011002,0.01669029,0.00005330847,0.00001351832,0.00005035971,0.00004684525,0.00002206731,0.003993062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01244043,"threshold_uncertainty_score":0.02473605,"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."}}