{"id":"W1989454011","doi":"10.1016/j.mcm.2006.09.025","title":"Non-causal models in long term planning via set contractive optimal control methods","year":2006,"lang":"en","type":"article","venue":"Mathematical and Computer Modelling","topic":"Water resources management and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Université du Québec à Montréal","funders":"","keywords":"Term (time); Set (abstract data type); Mathematics; Control (management); Computer science; Mathematical optimization; Applied mathematics; Artificial intelligence","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":[0.0001967153,0.000179485,0.0002814162,0.0001025919,0.00004284041,0.0001089938,0.00008607148,0.00007022735,0.000006262087],"category_scores_gemma":[4.56751e-7,0.000162332,0.00003844397,0.00007152194,0.00002121882,0.0002285303,0.0000386866,0.0001454335,0.000004123285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002077393,"about_ca_system_score_gemma":0.00000147712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007039569,"about_ca_topic_score_gemma":4.380596e-7,"domain_scores_codex":[0.9991211,0.00002547982,0.0003011603,0.0001879717,0.0001021779,0.0002621448],"domain_scores_gemma":[0.9997281,0.00008648091,0.00003002258,0.00009505585,0.00001421631,0.00004605685],"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":[0.00001181466,0.00002791586,0.0001159372,0.0001117985,0.00002668702,0.00001668467,0.0005685829,0.9961486,0.00003385636,0.001430532,0.000009600506,0.001497932],"study_design_scores_gemma":[0.0006150156,0.00001732947,0.0001613725,0.0001057725,0.00002519944,0.000005965431,0.000009323639,0.9855145,0.0001057119,0.013243,0.000005026221,0.0001918428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1443578,0.00009553476,0.8543423,0.000009979085,0.00003740286,0.0002014098,0.000001059486,0.0001026718,0.0008517815],"genre_scores_gemma":[0.7824297,0.000003810675,0.2173837,0.00001777956,0.0000913164,0.00001585874,0.000009032833,0.00002255875,0.0000262656],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6380718,"threshold_uncertainty_score":0.6619709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969220805337969,"score_gpt":0.2436175171979093,"score_spread":0.2239253091445296,"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."}}