{"id":"W2990431717","doi":"","title":"The Probability Distribution of Land Surface Wind Speeds","year":2011,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Wind shear; Weibull distribution; Wind speed; Wind profile power law; Atmospheric sciences; Meteorology; Thermal wind; Wind gradient; Planetary boundary layer; Environmental science; Log wind profile; Surface layer; Skewness; Boundary layer; Middle latitudes; Troposphere; Climatology; Geology; Mechanics; Turbulence; Mathematics; Physics; Statistics; Layer (electronics); Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001764177,0.0005284147,0.0004048416,0.001282319,0.0004392882,0.001358415,0.0006982853,0.0005792113,0.003934364],"category_scores_gemma":[0.009228206,0.0004196463,0.0005634513,0.001082833,0.0008723654,0.001656698,0.0006506016,0.0005607578,0.0008944613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007358575,"about_ca_system_score_gemma":0.0002968659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004613021,"about_ca_topic_score_gemma":0.002506616,"domain_scores_codex":[0.9992002,0.000141343,0.00005610079,0.0002531171,0.0002040906,0.00014524],"domain_scores_gemma":[0.99488,0.002773923,0.0007170167,0.0008929546,0.00060486,0.0001313013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005331688,0.0001417067,0.4449424,0.0002242966,0.0002238774,0.0007736286,0.0004586031,0.3835466,0.01208016,0.03941819,0.003802162,0.1138553],"study_design_scores_gemma":[0.00003990428,0.0001582827,0.2601131,0.00005839852,0.00003727595,0.0005236734,0.000252361,0.7062854,0.005462321,0.02352346,0.003412917,0.0001328626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8077586,0.000876263,0.1807569,0.000390474,0.00006390102,0.000209527,0.005025814,0.0008813822,0.004037227],"genre_scores_gemma":[0.9896582,0.0004264379,0.004616586,0.00002376203,0.0000494483,0.0001066695,0.003241224,0.00004606878,0.001831592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004613021,"threshold_uncertainty_score":0.01316172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02254018292642647,"score_gpt":0.2173750738115727,"score_spread":0.1948348908851462,"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."}}