{"id":"W7039258049","doi":"","title":"Lessons Learned Monitoring Near and Further From Wind Turbines","year":2023,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Noise Effects and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wind power; Microphone; Turbine; Annoyance; Wind speed; Noise (video); Wake; Sound (geography)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005495466,0.001293734,0.0006772588,0.001251713,0.001494213,0.002630654,0.003728399,0.002829021,0.005375458],"category_scores_gemma":[0.01468872,0.000443826,0.0009576575,0.0007161156,0.001248687,0.004130346,0.002581917,0.003980825,0.00273591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002176929,"about_ca_system_score_gemma":0.004123823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01537781,"about_ca_topic_score_gemma":0.0359552,"domain_scores_codex":[0.9958522,0.001342875,0.000323322,0.00086815,0.001128101,0.0004852453],"domain_scores_gemma":[0.987739,0.002700956,0.000517592,0.0007754511,0.00616062,0.002106213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001592824,0.0006819725,0.03531208,0.003192626,0.00008595241,0.002958754,0.01311426,0.0016336,0.005296658,0.002278416,0.1128684,0.822418],"study_design_scores_gemma":[0.0001003897,0.001975891,0.09903053,0.01015318,0.0002341713,0.009758027,0.1302746,0.004899476,0.01014265,0.0270495,0.7059635,0.0004181014],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2338107,0.04884972,0.07072064,0.5392744,0.02918235,0.001706715,0.003426447,0.002349725,0.07067931],"genre_scores_gemma":[0.5872276,0.0677429,0.1613866,0.09093908,0.01142319,0.001077588,0.002831253,0.000720669,0.07665101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01537781,"threshold_uncertainty_score":0.03057665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0977992806041288,"score_gpt":0.3999397899124447,"score_spread":0.3021405093083159,"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."}}