{"id":"W2114661994","doi":"10.1109/tec.2004.827718","title":"Generating Capacity Adequacy Associated With Wind Energy","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":345,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Wind power; Wind speed; Reliability (semiconductor); Monte Carlo method; Range (aeronautics); Electricity generation; Reliability engineering; Energy (signal processing); Computer science; Environmental science; Engineering; Power (physics); Meteorology; Statistics; Electrical engineering; Mathematics; Aerospace engineering","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":[0.00008972097,0.0002241018,0.000210078,0.0001115314,0.0001993968,0.00002578582,0.0001225175,0.0001647555,0.00006245659],"category_scores_gemma":[0.000003867266,0.0002066859,0.00009413211,0.0002751046,0.0000624563,0.0002199198,7.698717e-7,0.000186342,0.00001706682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004181296,"about_ca_system_score_gemma":0.00004424504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006797246,"about_ca_topic_score_gemma":0.0006261661,"domain_scores_codex":[0.998939,0.00004355838,0.0002124818,0.0002581245,0.0002282847,0.0003185096],"domain_scores_gemma":[0.9994589,0.00005407661,0.00004146913,0.000256676,0.00006740705,0.0001214896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002400974,0.00008863526,0.000003230463,0.00001920896,0.00008990809,0.0000117403,0.0001580247,0.9877158,0.0099391,0.0003241854,0.0001102611,0.0015159],"study_design_scores_gemma":[0.004027606,0.0005336434,0.000069748,0.0006430761,0.0001225105,0.00004722296,0.0001986034,0.1567193,0.8254547,0.0002517872,0.01086633,0.001065471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1893141,0.00004500003,0.8084423,0.00006140194,0.0008749025,0.00004495385,0.00001864129,0.0003995397,0.0007992052],"genre_scores_gemma":[0.9989469,0.00007263177,0.0003470303,0.000184323,0.00003835777,0.00001504665,0.00000757613,0.00003838023,0.0003497704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8309965,"threshold_uncertainty_score":0.8428409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008797977929852582,"score_gpt":0.1713806469302396,"score_spread":0.162582669000387,"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."}}