{"id":"W1851662160","doi":"10.1002/aic.15086","title":"Hybrid model for optimization of crude oil distillation units","year":2015,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Process Optimization and Integration","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Ontario Research Foundation; McMaster University","keywords":"Distillation; Boiling point; Vacuum distillation; Process engineering; Heat exchanger; Mean squared error; Fractionating column; Boiling; Petroleum engineering; Engineering; Chemistry; Mathematics; Mechanical engineering; Chromatography; Statistics","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":[0.0004575191,0.0007885702,0.001001498,0.0004339975,0.0004498038,0.001197073,0.001214225,0.001490692,0.004704176],"category_scores_gemma":[0.0008186685,0.0006165915,0.0009058348,0.0005454955,0.0005529597,0.0006088649,0.0008097424,0.001088341,0.0006971628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001038032,"about_ca_system_score_gemma":0.001523817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01868587,"about_ca_topic_score_gemma":0.01049477,"domain_scores_codex":[0.9997709,0.00005990766,0.00001087841,0.00004898136,0.0000702551,0.00003914505],"domain_scores_gemma":[0.9996364,0.0002015911,0.0000354405,0.00002543139,0.00008194835,0.0000191413],"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":[0.00001512569,0.000006147373,0.00008238015,0.000008714028,0.000004898361,0.000008083705,0.000003914728,0.9978606,0.0002253011,0.0007149456,0.00007536952,0.0009945035],"study_design_scores_gemma":[0.000003530887,0.000004948497,0.00002882501,8.460699e-7,0.000001486774,0.00000107116,0.000001405249,0.9994836,0.00009985116,0.0002221049,0.0001508073,0.000001371951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1104043,0.0005328116,0.8483693,0.0003763581,0.00009967425,0.0002032029,0.001414887,0.001387664,0.0372118],"genre_scores_gemma":[0.927124,0.0002437756,0.05353572,0.0000877877,0.00002814039,0.0006483141,0.0008337636,0.0001362928,0.01736216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01868587,"threshold_uncertainty_score":0.0371542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04124078487906657,"score_gpt":0.2487570674018649,"score_spread":0.2075162825227984,"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."}}