{"id":"W2956025531","doi":"10.3390/en12132472","title":"A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks","year":2019,"lang":"en","type":"article","venue":"Energies","topic":"Water resources management and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Fundamental Research Funds for the Central Universities","keywords":"Mathematical optimization; Renewable energy; Stochastic programming; Fuzzy logic; Electricity generation; Robustness (evolution); Computer science; Linear programming; Electricity; Robust optimization; Engineering; Power (physics); 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":[0.00008792326,0.000101142,0.0001418887,0.000103101,0.00002643271,0.00002456311,0.00005881349,0.00003804748,0.000009276718],"category_scores_gemma":[0.000001561337,0.00009164302,0.00002934697,0.0001022661,0.000010107,0.0000868585,0.00002485457,0.0000277389,0.000001087301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002787503,"about_ca_system_score_gemma":0.000002679274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008631215,"about_ca_topic_score_gemma":0.000004476025,"domain_scores_codex":[0.9995345,0.00001204584,0.0001492875,0.0001152154,0.00007887367,0.0001100144],"domain_scores_gemma":[0.9997999,0.00002164555,0.00003151907,0.00008846764,0.00004364856,0.00001480912],"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":[0.00002700059,0.00000321727,0.00003203487,0.000404373,0.0001368674,3.667727e-7,0.000113972,0.9648521,0.0002880922,0.03055217,0.00007145222,0.003518367],"study_design_scores_gemma":[0.0002938796,0.00002147249,0.00001219847,0.0001047061,0.00003658831,6.17881e-7,0.001675871,0.9936686,0.001298094,0.0002934076,0.002493454,0.0001011431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1614512,0.0005417512,0.8288746,0.00001585651,0.0003763692,0.000192856,0.0000110859,0.0002244857,0.008311703],"genre_scores_gemma":[0.9579152,0.0001581966,0.04079256,0.000005245796,0.00003117454,0.00003379711,0.00005615836,0.00001920026,0.0009885032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7964639,"threshold_uncertainty_score":0.3737094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755663701878073,"score_gpt":0.2350386641728025,"score_spread":0.2174820271540218,"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."}}