{"id":"W2901553932","doi":"10.1109/tpwrs.2018.2881250","title":"A Hybrid Framework for Short-Term Risk Assessment of Wind-Integrated Composite Power Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability engineering; Electric power system; Reliability (semiconductor); Wind power; Monte Carlo method; Computer science; Transmission system; Term (time); Cross entropy; Power system simulation; Entropy (arrow of time); Mathematical optimization; Engineering; Transmission (telecommunications); Principle of maximum entropy; Power (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001900986,0.001312599,0.001036731,0.001304102,0.0004200009,0.001325101,0.001681899,0.0008366901,0.001767329],"category_scores_gemma":[0.002486306,0.000464189,0.001287913,0.0007933798,0.0006189564,0.001636107,0.001181757,0.0010212,0.0002838652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008178042,"about_ca_system_score_gemma":0.001441121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004324462,"about_ca_topic_score_gemma":0.003704443,"domain_scores_codex":[0.9990578,0.0004027107,0.00004501577,0.0001019977,0.0003267045,0.00006575943],"domain_scores_gemma":[0.9991468,0.0004514224,0.00009316855,0.00005904879,0.0001964591,0.00005314115],"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":[0.00001136721,0.00001730476,0.0002468551,0.00003612771,0.00003736635,0.00005804914,0.00002979193,0.9418732,0.0006154208,0.04477027,0.0003500456,0.01195409],"study_design_scores_gemma":[0.000002058142,0.00001161915,0.00004418006,0.000005266325,0.000006005838,0.00001522054,0.000005019368,0.9900317,0.00007240808,0.009334171,0.0004670525,0.000005253795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002299493,0.0001716489,0.9964624,0.00003489718,0.0000133011,0.00001600172,0.00002473743,0.00005221091,0.0009254031],"genre_scores_gemma":[0.4975595,0.001332256,0.4955269,0.00008702551,0.0002081796,0.0004529738,0.000322618,0.0001637713,0.004346848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004324462,"threshold_uncertainty_score":0.01005352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01149508324924339,"score_gpt":0.2568713865858105,"score_spread":0.2453763033365671,"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."}}