{"id":"W2041456605","doi":"10.1002/cjce.5450850107","title":"Steady‐State Reactive Distillation Simulation Using the Naphtali‐Sandholm Method","year":2007,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reactive distillation; Steady state (chemistry); Column (typography); Work (physics); Distillation; Fractionating column; Process engineering; Chemistry; Computer science; Chromatography; Engineering; Organic chemistry; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004533929,0.000318448,0.0005845398,0.0002337428,0.000420808,0.0005075113,0.0007002131,0.0006192673,0.002135478],"category_scores_gemma":[0.001026868,0.0002926805,0.0004448496,0.0002548526,0.000440255,0.0003648987,0.0002827109,0.0005118006,0.0002157839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006869982,"about_ca_system_score_gemma":0.001065289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687179,"about_ca_topic_score_gemma":0.008539469,"domain_scores_codex":[0.9998902,0.00003104763,0.000005739298,0.00001425995,0.00003265325,0.00002613164],"domain_scores_gemma":[0.9991537,0.000606158,0.00004662751,0.00004466761,0.0001214603,0.0000273665],"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":[0.00008701935,0.00004526355,0.0008532669,0.00003129054,0.0000147123,0.00003469594,0.00003600994,0.9901333,0.004075152,0.002673951,0.0001126761,0.001902697],"study_design_scores_gemma":[0.000006406235,0.00001004494,0.00009560199,8.274822e-7,0.000001651489,0.000001396667,0.000005064565,0.9987828,0.0008904379,0.0001173101,0.00008605997,0.000002377828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8482527,0.00009845552,0.1373461,0.0001862718,0.00003933628,0.0001102065,0.0004580173,0.0004518772,0.01305715],"genre_scores_gemma":[0.973008,0.00006733867,0.02399641,0.00002509004,0.000004547647,0.0001350026,0.0002046863,0.00004512229,0.002513739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01687179,"threshold_uncertainty_score":0.03354716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491759855138418,"score_gpt":0.2543337546706595,"score_spread":0.2394161561192753,"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."}}