{"id":"W17731937","doi":"10.1016/b978-0-444-63456-6.50048-x","title":"Inventory Pinch Based Multi-Scale Model for Refinery Production Planning","year":2014,"lang":"en","type":"book-chapter","venue":"Computer-aided chemical engineering/Computer aided chemical engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Refinery; Pinch analysis; Production (economics); Mathematical optimization; Production planning; Integer (computer science); Computer science; Nonlinear system; Decomposition; Scale (ratio); Work (physics); Plan (archaeology); Algorithm; Mathematics; Engineering; Process engineering; Waste management; Economics","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":[0.0004591912,0.000964243,0.002042498,0.0005063699,0.0006726595,0.001509642,0.002633907,0.00155347,0.01034686],"category_scores_gemma":[0.0006960101,0.001059341,0.001336694,0.001376232,0.0005846557,0.001583613,0.000954251,0.001643091,0.001121614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001875937,"about_ca_system_score_gemma":0.001735474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03575421,"about_ca_topic_score_gemma":0.02438478,"domain_scores_codex":[0.999768,0.00006449977,0.00001114226,0.00005009431,0.00006781019,0.0000385636],"domain_scores_gemma":[0.9997327,0.0001510909,0.00002121895,0.00001837789,0.00005927762,0.00001741159],"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":[0.00001196298,0.00000744304,0.00003774358,0.00001609054,0.000005539955,0.00001144077,0.000003895727,0.9965889,0.00009983448,0.0009581098,0.0002444437,0.002014456],"study_design_scores_gemma":[0.000003036289,0.00000506143,0.00002136049,0.000001715197,0.000002595761,0.000002064888,0.000001354649,0.9991474,0.00004560795,0.0005982963,0.000169517,0.000002032262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03779846,0.001961246,0.9188098,0.0005068589,0.0002009176,0.0001797635,0.00176211,0.001415331,0.03736553],"genre_scores_gemma":[0.8450586,0.00157211,0.11358,0.0001797013,0.00008221515,0.0005956597,0.001330424,0.0003096061,0.03729168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03575421,"threshold_uncertainty_score":0.07109219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0190980412339993,"score_gpt":0.2056008408318987,"score_spread":0.1865027995978994,"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."}}