{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001536434,0.001242913,0.001463762,0.001025829,0.0007531608,0.001712384,0.001604053,0.001497207,0.003718121],"category_scores_gemma":[0.002804024,0.0009598471,0.0008430174,0.001044523,0.001108953,0.002148089,0.001828588,0.001110101,0.0003440696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002285734,"about_ca_system_score_gemma":0.002882292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005703573,"about_ca_topic_score_gemma":0.006014088,"domain_scores_codex":[0.9987326,0.0004384217,0.00004377543,0.0003462993,0.0002227425,0.0002160375],"domain_scores_gemma":[0.9989793,0.0004507604,0.0002183228,0.00006904327,0.0001621526,0.0001204521],"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":[0.00002508687,0.00002611101,0.0002168483,0.00002402111,0.00001286964,0.0000406218,0.00001706545,0.9887554,0.0007354697,0.004974377,0.0001024554,0.005069543],"study_design_scores_gemma":[0.00001801182,0.00005088126,0.0001201884,0.000006123335,0.00001193651,0.0000185377,0.00002726669,0.9946539,0.0005692159,0.003902471,0.000614861,0.0000065963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05628023,0.0002788751,0.9352586,0.0002137494,0.00002673388,0.0001726385,0.00008131682,0.0001367428,0.007551289],"genre_scores_gemma":[0.8005835,0.0003933738,0.1940214,0.00005884993,0.00002646901,0.0003315672,0.0001344817,0.00008654116,0.004363863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005703573,"threshold_uncertainty_score":0.01658422,"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."}}