{"id":"W2052283622","doi":"10.1081/drt-120025500","title":"Synthesis of Rice Processing Plants. II. MINLP Optimization","year":2003,"lang":"en","type":"article","venue":"Drying Technology","topic":"Process Optimization and Integration","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Process engineering; Tempering; Energy consumption; Nonlinear programming; Mathematical optimization; Mathematics; Engineering; Nonlinear system; Materials science","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":[0.001100429,0.0008701485,0.0008385813,0.0006981755,0.0004992083,0.001174409,0.000639476,0.0006992182,0.007593235],"category_scores_gemma":[0.001713858,0.0006422354,0.001001331,0.0007704265,0.0004802466,0.0006265796,0.0006395714,0.0008952479,0.001272192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114052,"about_ca_system_score_gemma":0.001704962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002089189,"about_ca_topic_score_gemma":0.003187023,"domain_scores_codex":[0.9994169,0.0002169195,0.00002765937,0.0001056435,0.0001618517,0.00007097254],"domain_scores_gemma":[0.9994724,0.000269969,0.00008486456,0.00004096162,0.0001106912,0.00002111218],"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":[0.00007077845,0.00005417919,0.0002472004,0.0004677432,0.00002347368,0.00008596302,0.000054606,0.9216966,0.009922376,0.01517885,0.001185067,0.05101325],"study_design_scores_gemma":[0.00003374711,0.0002660273,0.000197948,0.0000500852,0.00002090277,0.00004968719,0.00005444127,0.9646042,0.01102417,0.01399574,0.009690307,0.00001272566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02533939,0.000594535,0.9483833,0.0002214118,0.00005706915,0.0003500051,0.0005550673,0.0005663683,0.02393277],"genre_scores_gemma":[0.2831408,0.0007573428,0.7050281,0.0001196095,0.00003732012,0.0009973301,0.0009034101,0.0002024406,0.00881361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007593235,"threshold_uncertainty_score":0.02540195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006815533267386991,"score_gpt":0.2030635798819491,"score_spread":0.1962480466145621,"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."}}