{"id":"W2090493490","doi":"10.1021/ie801001q","title":"Multisite Refinery and Petrochemical Network Design: Optimal Integration and Coordination","year":2008,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Process Optimization and Integration","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Petrochemical; Oil refinery; Refinery; Refining (metallurgy); Process integration; Process (computing); Production (economics); Process engineering; Computer science; Engineering; Waste management; Chemistry","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":[0.0004171703,0.000165885,0.000160177,0.00008134007,0.0001327012,0.00007856456,0.00009478967,0.0002900392,0.00002998845],"category_scores_gemma":[0.00053489,0.0001751561,0.00001922685,0.0003846924,0.00007932504,0.0002247856,0.00004450681,0.0007467179,0.000003097028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109874,"about_ca_system_score_gemma":0.00002961572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000854611,"about_ca_topic_score_gemma":3.316148e-7,"domain_scores_codex":[0.9989256,0.00002389853,0.0002250215,0.0002269675,0.0002707722,0.0003277459],"domain_scores_gemma":[0.9993908,0.0001735666,0.00001874816,0.0001201965,0.0001519737,0.0001447614],"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":[0.0000419857,0.00001329729,0.0001944233,0.00005342924,0.00002322947,0.000009126429,0.0001261456,0.3773149,0.6121968,0.00004327573,0.007278446,0.002704915],"study_design_scores_gemma":[0.0004721511,0.00002400419,0.00006810999,0.00006985279,0.000004260382,0.00005247292,0.00002648044,0.6948413,0.3027817,0.000007020755,0.001488825,0.0001637719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9060532,0.001162103,0.09022499,0.0002205114,0.0002325075,0.0004128781,0.000009957424,0.0006132963,0.001070534],"genre_scores_gemma":[0.9954122,0.0003300901,0.003128888,0.000003746804,0.0005975435,0.00005195956,0.00005551163,0.00003666206,0.0003834394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3175264,"threshold_uncertainty_score":0.7142658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08645292320185455,"score_gpt":0.290064867647191,"score_spread":0.2036119444453365,"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."}}