{"id":"W2127630762","doi":"10.1007/s00477-012-0657-y","title":"Inexact stochastic dynamic programming method and application to water resources management in Shandong China under uncertainty","year":2012,"lang":"en","type":"article","venue":"Stochastic Environmental Research and Risk Assessment","topic":"Water resources management and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina; University of Northern British Columbia","funders":"","keywords":"Computer science; Water resources; Stochastic programming; Constraint (computer-aided design); Reliability (semiconductor); Probabilistic logic; Context (archaeology); Mathematical optimization; Interval (graph theory); Water scarcity; Operations research; Water supply; Risk management; Joint (building); Environmental science; Civil engineering; Mathematics; Environmental engineering; Engineering; Economics","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":[0.001085705,0.0002159885,0.0001786427,0.0003753956,0.0002251642,0.0001155937,0.0001275665,0.00005808587,0.00002465395],"category_scores_gemma":[0.0000048603,0.000170435,0.00002081787,0.0001654207,0.00009390836,0.0001923735,0.000346671,0.0003175034,0.00001570965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003542331,"about_ca_system_score_gemma":0.00000168303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007516088,"about_ca_topic_score_gemma":0.00004412362,"domain_scores_codex":[0.9981061,0.0001146744,0.0002381209,0.0003473423,0.00046034,0.0007334434],"domain_scores_gemma":[0.9994558,0.00006325912,0.00002355476,0.0002030367,0.00000475452,0.0002495781],"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":[0.00004664349,0.0001388647,0.004833059,0.00007263039,0.00007904707,0.000001863593,0.00197191,0.9291387,0.0003045402,0.0001083615,0.000006487706,0.06329788],"study_design_scores_gemma":[0.001009896,0.000215842,0.1743189,0.00006128127,0.00005448064,0.000004139415,0.002232929,0.8202912,0.00002719353,0.0009219422,0.0005039802,0.0003582387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4081521,0.0001967648,0.5903535,0.00005971342,0.00002666631,0.0009987655,0.000006051515,0.000037449,0.0001689987],"genre_scores_gemma":[0.9903939,0.0002302568,0.008594282,0.000007643745,0.00003788794,0.0004664112,0.00006260087,0.00003911483,0.0001679284],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5822418,"threshold_uncertainty_score":0.6950138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009068550560283679,"score_gpt":0.2977681149226046,"score_spread":0.288699564362321,"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."}}