{"id":"W2417775511","doi":"10.1177/0309524x16653486","title":"Urban wind resource assessment in changing climate: Case study","year":2016,"lang":"en","type":"article","venue":"Wind Engineering","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Wind speed; Urban climate; Climate change; Environmental science; Wind power; Resource (disambiguation); Wind resource assessment; Meteorology; Prevailing winds; Geography; Wind direction; Climatology; Urban planning; Environmental resource management; Civil engineering; Geology; Engineering; Computer science; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004135425,0.0003918572,0.0003030523,0.0006198115,0.0008243741,0.0008144361,0.0006750511,0.001106011,0.0009844289],"category_scores_gemma":[0.0006884073,0.0001834841,0.0005047286,0.002077771,0.0005668176,0.0004491589,0.0006207523,0.0003217302,0.0001120347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002040449,"about_ca_system_score_gemma":0.0007616502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09500676,"about_ca_topic_score_gemma":0.1499694,"domain_scores_codex":[0.9997376,0.00009482037,0.00001393657,0.00003570522,0.00005244185,0.00006546628],"domain_scores_gemma":[0.9996446,0.0001719062,0.00003844421,0.00003391719,0.00005647253,0.00005452104],"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":[0.0001188459,0.0002557449,0.0368931,0.0001325819,0.00005768779,0.004130427,0.000460642,0.9354497,0.001797627,0.003219238,0.001379707,0.01610471],"study_design_scores_gemma":[0.00006293068,0.0001996783,0.04709617,0.00003608464,0.00007189466,0.0005786998,0.003492404,0.9377174,0.00322088,0.002314546,0.005137105,0.00007213559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849396,0.0001658316,0.009576553,0.0001543851,0.00001393426,0.0001046345,0.000480585,0.000066903,0.00449762],"genre_scores_gemma":[0.9936201,0.000168517,0.005106687,0.00001102176,0.000007401493,0.00003600225,0.0001763542,0.000008444004,0.0008655484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09500676,"threshold_uncertainty_score":0.1889075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008092915356394692,"score_gpt":0.2194502314024035,"score_spread":0.2113573160460088,"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."}}