{"id":"W4405930877","doi":"10.1016/j.compfluid.2024.106537","title":"Characterization of atmospheric and wind farm turbulence","year":2024,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Turbulence; Environmental science; Meteorology; Atmospheric turbulence; Characterization (materials science); Atmospheric sciences; Mathematics; Geology; Physics; Optics","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":[0.0003413017,0.0002973673,0.0003640668,0.0004280525,0.0002754141,0.0007499433,0.0003217171,0.0004376017,0.0003930945],"category_scores_gemma":[0.0008257047,0.0001756739,0.0003724665,0.0005270831,0.0003305722,0.0009017526,0.0003665139,0.0003467599,0.00007898003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003291596,"about_ca_system_score_gemma":0.0005607955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00531983,"about_ca_topic_score_gemma":0.006056204,"domain_scores_codex":[0.9997908,0.00003361146,0.00001738814,0.00005696407,0.00007091153,0.00003030231],"domain_scores_gemma":[0.9997023,0.0001125562,0.00004788953,0.00005962694,0.00004925055,0.00002837929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00005517899,0.0001272701,0.04193755,0.00003840614,0.00003703309,0.00008575516,0.00005714602,0.9179137,0.02138756,0.002301987,0.0002554828,0.01580284],"study_design_scores_gemma":[0.000005592142,0.00002940273,0.01373393,0.000002149885,0.000003921546,0.00001176687,0.00002150725,0.9839977,0.001617981,0.0003916553,0.0001754615,0.000008898095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386576,0.00009090745,0.05779539,0.00005031771,0.00002037868,0.0000415469,0.0002844872,0.0002107711,0.002848703],"genre_scores_gemma":[0.9940799,0.00004952728,0.00540668,0.000006673162,0.000003819625,0.00001445613,0.0001955415,0.00001285937,0.0002304543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00531983,"threshold_uncertainty_score":0.01057774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005539018425663779,"score_gpt":0.1946181266768405,"score_spread":0.1890791082511767,"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."}}