{"id":"W1980331469","doi":"10.1016/j.jweia.2006.05.008","title":"The r largest order statistics model for extreme wind speed estimation","year":2006,"lang":"en","type":"article","venue":"Journal of Wind Engineering and Industrial Aerodynamics","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University Network of Excellence in Nuclear Engineering","keywords":"Gumbel distribution; Extreme value theory; Wind speed; Statistics; Poisson distribution; Generalized extreme value distribution; Maxima; Order statistic; Mathematics; Meteorology; Estimation; Geography; Engineering","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":[0.00782893,0.001185528,0.002365871,0.0008751467,0.0005973934,0.00150946,0.002299379,0.001820009,0.002080529],"category_scores_gemma":[0.02377142,0.001243831,0.001466129,0.001117646,0.001188892,0.002711935,0.001360702,0.00288265,0.001456174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006744774,"about_ca_system_score_gemma":0.001698191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006239709,"about_ca_topic_score_gemma":0.004834938,"domain_scores_codex":[0.9968523,0.002087509,0.0001545251,0.0003973401,0.0003238731,0.000184503],"domain_scores_gemma":[0.9813212,0.01521765,0.0008199783,0.001406371,0.0010259,0.0002089316],"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":[0.0002759743,0.00007047186,0.001279411,0.0001050334,0.000188245,0.00008463563,0.00006193102,0.8977545,0.001492825,0.03907394,0.002199702,0.05741324],"study_design_scores_gemma":[0.000006064931,0.00001701659,0.0001481981,0.000003717881,0.000008071454,0.00000808119,0.00000249851,0.9930916,0.0001516878,0.006369796,0.0001846617,0.000008725317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007719919,0.0002593507,0.9910829,0.0001776952,0.00003617085,0.00001411239,0.00009213184,0.0003064259,0.0003113182],"genre_scores_gemma":[0.6616325,0.001359005,0.3239964,0.0004319331,0.000555739,0.0003343611,0.001989903,0.0006102662,0.009089837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00782893,"threshold_uncertainty_score":0.04140389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897827943353317,"score_gpt":0.2073260152957569,"score_spread":0.1883477358622237,"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."}}