{"id":"W2604437513","doi":"10.1061/9780784480410.003","title":"Wind Load Prediction on Tall Buildings in a Stochastic Framework","year":2017,"lang":"en","type":"article","venue":"Structures Congress 2017","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rowan Williams Davies & Irwin (Canada)","funders":"","keywords":"Wind engineering; Reliability (semiconductor); Wind speed; Wind power; Stochastic process; Wind tunnel; Set (abstract data type); Computer science; Natural frequency; Range (aeronautics); Marine engineering; Environmental science; Engineering; Structural engineering; Meteorology; Vibration; Mathematics; Aerospace engineering; Statistics","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":[0.0001102351,0.000187716,0.0001869791,0.00002991338,0.0005986207,0.0001453254,0.0005367239,0.0001256138,0.0004778639],"category_scores_gemma":[0.0003525507,0.0001523121,0.00004910893,0.00003306471,0.0004578488,0.0002454257,0.0003129567,0.0002911207,0.0001343395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001203554,"about_ca_system_score_gemma":0.00001074598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002896181,"about_ca_topic_score_gemma":0.0001711541,"domain_scores_codex":[0.9987537,0.00001841615,0.0001515187,0.0003879345,0.0003701279,0.0003183634],"domain_scores_gemma":[0.9991226,0.00004740625,0.0001513781,0.0005921632,0.000008702905,0.00007779596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007002663,0.0002543002,0.7730809,0.00006625066,0.0001815771,0.0003374069,0.006202536,0.0633808,0.008179375,0.01020912,0.06629322,0.07111429],"study_design_scores_gemma":[0.0005734561,0.0001073633,0.9742157,0.0001410464,0.00001260095,0.000007596414,0.00005530872,0.0004624335,0.0003415626,0.01908606,0.004751462,0.0002453621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844256,0.00005766695,0.0001334778,0.0004287196,0.001393323,0.0002110529,0.0000344279,0.00003512457,0.01328058],"genre_scores_gemma":[0.9987012,0.00001149853,0.0002549626,0.0001300119,0.0001869821,0.000008430108,0.000001821307,0.00001279397,0.0006922705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2011349,"threshold_uncertainty_score":0.6211107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343714017803906,"score_gpt":0.2614591091028766,"score_spread":0.2480219689248375,"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."}}