{"id":"W4232229023","doi":"10.32920/ryerson.14653311.v1","title":"Modeling of Gust Energy Extractions through Aeroelastic Tailoring","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Aeroelasticity; Energy (signal processing); Structural engineering; Computer science; Engineering; Aerospace engineering; Aerodynamics; Physics","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":[0.000199752,0.0007698488,0.000713282,0.0004112596,0.0005164677,0.001078441,0.0008539781,0.001274989,0.001966512],"category_scores_gemma":[0.0007182704,0.0005092174,0.0008467864,0.0005628748,0.0005864797,0.00104864,0.0007162921,0.0006521763,0.0002170697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000848994,"about_ca_system_score_gemma":0.0008544241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03365917,"about_ca_topic_score_gemma":0.01036335,"domain_scores_codex":[0.9998833,0.0000186735,0.000007585653,0.00002198746,0.00003342654,0.00003502977],"domain_scores_gemma":[0.9998003,0.00008170433,0.00003103262,0.00001740872,0.00004208181,0.00002752559],"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":[0.00001634449,0.00001050147,0.0002917642,0.000007672468,0.000007046524,0.00003073422,0.000008219075,0.9971241,0.001198107,0.0005325346,0.00003566895,0.0007373016],"study_design_scores_gemma":[0.000003636177,0.00000444368,0.0001821752,0.000001093439,0.000002297673,0.000003508301,0.000003202281,0.9992682,0.0002833127,0.0001829401,0.00006295751,0.000002241551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7007507,0.0006598376,0.256899,0.0004627912,0.00008039126,0.0001351344,0.0007610348,0.0006948144,0.03955637],"genre_scores_gemma":[0.9906786,0.0002219432,0.002732694,0.0000233334,0.00001173774,0.00002956789,0.0001264047,0.00005780483,0.006117859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03365917,"threshold_uncertainty_score":0.06692648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03269993415056117,"score_gpt":0.2463806100155055,"score_spread":0.2136806758649443,"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."}}