{"id":"W3165596616","doi":"10.1002/aic.17333","title":"Multistage adaptive stochastic mixed integer optimization under endogenous and exogenous uncertainty","year":2021,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Process Optimization and Integration","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Robust optimization; Affine transformation; Stochastic optimization; Stochastic programming; Optimization problem; Set (abstract data type); Mathematics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001166821,0.0001421481,0.0001463867,0.00008138675,0.0001531512,0.0001290264,0.00006498984,0.00008553681,0.0002630496],"category_scores_gemma":[0.00009412655,0.0001331005,0.00003898781,0.0001692568,0.00002827396,0.0002586747,0.00001862795,0.0002946443,0.000009095432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001340635,"about_ca_system_score_gemma":0.00007862574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000583003,"about_ca_topic_score_gemma":0.00002989161,"domain_scores_codex":[0.9992552,0.00004591339,0.0002388515,0.0001233948,0.0001476078,0.0001890337],"domain_scores_gemma":[0.9994075,0.00004869069,0.00005610672,0.00008979149,0.0002805584,0.0001173664],"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":[0.00001214969,0.00002166642,0.000005426727,0.000008646763,0.00005488775,0.0000233818,0.0005269359,0.994593,0.002248307,0.0003127165,0.0002354068,0.001957475],"study_design_scores_gemma":[0.0005034159,0.00004235165,0.00003679863,0.00003566728,0.00003410639,0.0007371544,0.001221133,0.9949954,0.001848563,0.0002308186,0.0001462601,0.0001683708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005174561,0.00161958,0.9911005,0.00008721695,0.0003549385,0.00006955615,0.000008600506,0.00008741537,0.001497655],"genre_scores_gemma":[0.9825739,0.0005370121,0.01632778,0.0001591488,0.0001146458,0.000005886405,0.00003017978,0.00003193342,0.0002195234],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9773993,"threshold_uncertainty_score":0.5427682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02363440398510633,"score_gpt":0.2117548396958996,"score_spread":0.1881204357107933,"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."}}