{"id":"W1993497069","doi":"10.1002/ceat.201200048","title":"Semicontinuous Thermal Separation Systems","year":2012,"lang":"en","type":"article","venue":"Chemical Engineering & Technology","topic":"Process Optimization and Integration","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Extractive distillation; Distillation; Process engineering; Separation (statistics); Air separation; Batch distillation; Ternary operation; Process (computing); Separation process; Computer science; Fractional distillation; Engineering; Chemistry; Chromatography; Chemical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00004588739,0.0001315108,0.0001344706,0.0001366509,0.0000138984,0.00001660262,0.0001175305,0.000255035,0.00001843511],"category_scores_gemma":[0.00005325976,0.0001334878,0.00002413995,0.000263995,0.00001769135,0.0001799198,0.0000173665,0.0002109804,0.00005995188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007934896,"about_ca_system_score_gemma":0.000004163617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.273286e-7,"about_ca_topic_score_gemma":2.318344e-8,"domain_scores_codex":[0.9993973,0.000001857822,0.0001686748,0.00008791262,0.00006386001,0.0002804343],"domain_scores_gemma":[0.9997411,0.00001112724,0.00001667475,0.0001422973,0.00003190378,0.00005691464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001242923,0.00001381048,0.0001345496,0.00004990331,0.00001899062,4.168358e-7,0.00005559662,0.2244004,0.7687541,0.004675433,0.0006469779,0.001248526],"study_design_scores_gemma":[0.0001082568,0.000005630231,0.00001635163,0.00001999556,0.000007399748,0.00002094857,0.00001632862,0.5460678,0.4450472,0.00000928308,0.00850829,0.0001724942],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6773096,0.003869117,0.3075196,0.00009066746,0.001165404,0.0002107972,0.000004386011,0.005319544,0.004510907],"genre_scores_gemma":[0.9978744,0.00001979545,0.001785661,0.00001009297,0.0001511211,0.00005859231,0.00001838875,0.00003321478,0.00004867485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3237069,"threshold_uncertainty_score":0.5443473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004045069835445797,"score_gpt":0.1961787727590584,"score_spread":0.1921337029236126,"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."}}