{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005338508,0.0001026939,0.000108199,0.0001153515,0.00007230806,0.00006329783,0.0001410005,0.000056823,0.00001295122],"category_scores_gemma":[0.0002133422,0.00006790542,0.00005372223,0.0002450509,0.00002406452,0.0002020388,0.000003885543,0.0003051302,9.400678e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000302695,"about_ca_system_score_gemma":0.00007755235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000163814,"about_ca_topic_score_gemma":0.0001232338,"domain_scores_codex":[0.9993162,0.00001154507,0.0002913816,0.00004854958,0.0001416227,0.0001906936],"domain_scores_gemma":[0.9993535,0.0001753943,0.00007886571,0.00008767418,0.0001514033,0.0001531826],"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":[0.000005105449,7.968579e-7,0.00001456421,0.000006952615,0.00002352501,0.000002567714,0.0005879125,0.9720874,0.02554791,0.0001498265,0.00001746194,0.001556017],"study_design_scores_gemma":[0.0001008746,0.000005005606,0.00006889104,0.0000352784,0.0000192104,0.0000406518,0.00003928144,0.9425821,0.05623388,0.0001150991,0.0006763737,0.00008336677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1882674,0.0001965276,0.8107495,0.00009225406,0.000264188,0.00006979187,0.000003166211,0.00002613021,0.0003310318],"genre_scores_gemma":[0.9958456,0.000001629216,0.003915115,0.00003475769,0.0001700475,4.87536e-7,0.000002006467,0.00002219207,0.00000817868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8075781,"threshold_uncertainty_score":0.2769103,"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."}}