{"id":"W2120504822","doi":"10.1002/aic.14473","title":"Design under uncertainty using parallel multiperiod dynamic optimization","year":2014,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Discretization; Interval (graph theory); Mathematical optimization; Realization (probability); Solver; Computer science; Process (computing); Dynamic programming; Optimal control; Shooting method; Control theory (sociology); Control (management); Mathematics; Boundary value problem","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000493149,0.0001609666,0.0002078796,0.00009723072,0.0001541314,0.00008944623,0.0001257599,0.0001066417,0.00003328269],"category_scores_gemma":[0.00006635344,0.0001539564,0.00006023165,0.0001341003,0.00001933216,0.0003546243,0.00001097117,0.0002529966,0.00001096971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000258567,"about_ca_system_score_gemma":0.00002866374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004076385,"about_ca_topic_score_gemma":0.00000355586,"domain_scores_codex":[0.9988962,0.0001722648,0.0003930815,0.0001194644,0.000161042,0.0002579771],"domain_scores_gemma":[0.9994251,0.0000749122,0.0001251939,0.0001582524,0.0001100939,0.0001064495],"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":[0.00001184571,0.000006922402,0.00004644263,0.000006362003,0.00004487583,0.000001547146,0.00006612334,0.9955278,0.001762036,0.00002199788,0.00004054367,0.002463483],"study_design_scores_gemma":[0.0009089459,0.00002658287,0.00008133035,0.00003365733,0.00002845021,0.00009718734,0.00005299879,0.998219,0.00002073345,0.0002217598,0.0001303883,0.000178939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003586382,0.0002883739,0.995008,0.00004055145,0.0006160065,0.0001530811,5.316141e-7,0.0001516906,0.000155411],"genre_scores_gemma":[0.6122202,0.00009993696,0.3873496,0.00005284537,0.00018304,0.000003855745,0.000003381283,0.00004748975,0.00003958098],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6086339,"threshold_uncertainty_score":0.6278161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345752306823515,"score_gpt":0.2325897435764488,"score_spread":0.2191322205082137,"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."}}