{"id":"W2983504627","doi":"10.1515/revce-2018-0067","title":"Uncertainty in chemical process systems engineering: a critical review","year":2019,"lang":"en","type":"review","venue":"Reviews in Chemical Engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Uncertainty analysis; Merge (version control); Process (computing); Propagation of uncertainty; Multidisciplinary approach; Industrial engineering; Data mining; Uncertainty quantification; Risk analysis (engineering); Management science; Machine learning; Algorithm; Engineering; Simulation; Information retrieval","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":[0.003044951,0.001356352,0.002080799,0.003982764,0.0005040598,0.00164647,0.001422604,0.001726067,0.002143437],"category_scores_gemma":[0.004505064,0.000654946,0.0009922954,0.004296851,0.00115882,0.002303503,0.001082157,0.002003779,0.0008553993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001556207,"about_ca_system_score_gemma":0.003028136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002084098,"about_ca_topic_score_gemma":0.001887602,"domain_scores_codex":[0.9988638,0.000292205,0.0001810008,0.0001367371,0.0004652443,0.00006099093],"domain_scores_gemma":[0.9946405,0.003678404,0.0003164154,0.00009689439,0.001185753,0.00008203573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007989397,0.00007778234,0.0003483829,0.06555082,0.0003163851,0.000393745,0.0001950267,0.005135895,0.001265367,0.0317176,0.03790846,0.8570107],"study_design_scores_gemma":[0.00001481498,0.000181363,0.0009198139,0.02643258,0.0003981455,0.001086523,0.0001873866,0.001281503,0.001123709,0.02140095,0.9468799,0.00009322237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008165997,0.9980489,0.0006170484,0.0004441963,0.0002554666,0.000005879433,0.00001168799,0.000005076418,0.0005301199],"genre_scores_gemma":[0.001375418,0.9976423,0.0003516654,0.0001896671,0.0003045036,0.000008183868,0.00001430386,0.000001798735,0.0001120871],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003982764,"threshold_uncertainty_score":0.01610339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0490105961897821,"score_gpt":0.3273375912007691,"score_spread":0.278326995010987,"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."}}