{"id":"W1973409486","doi":"10.1016/j.energy.2010.04.049","title":"Optimum turbine-site matching","year":2010,"lang":"en","type":"article","venue":"Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Turbine; Tower; Weibull distribution; Matching (statistics); Marine engineering; Wind speed; Wind power; Small wind turbine; Power (physics); Engineering; Mathematics; Environmental science; Meteorology; Structural engineering; Statistics; Mechanical engineering; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006327301,0.00009565376,0.00007921692,0.00006881065,0.00004549092,0.00003732751,0.0001190387,0.00006027777,0.0003599619],"category_scores_gemma":[0.000007064346,0.00008769289,0.00002992687,0.00009918417,0.00001353872,0.00008125024,0.00003821362,0.0001763486,0.0001274414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001553502,"about_ca_system_score_gemma":0.00001678262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009646606,"about_ca_topic_score_gemma":0.0001648758,"domain_scores_codex":[0.999377,0.000005224884,0.00009352576,0.0001020038,0.0001397797,0.0002825099],"domain_scores_gemma":[0.9996585,0.00001709285,0.000005643912,0.0001682975,0.00001484639,0.000135678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002148987,0.00005838098,0.0006557725,0.00005285442,0.0001477453,0.0001768579,0.0007413902,0.2148755,0.5599212,0.05321811,0.06275257,0.1073781],"study_design_scores_gemma":[0.0003712389,0.00001846688,0.003210369,0.00001328612,0.000003108724,0.00003130628,0.00002307996,0.02146584,0.08607958,0.002663634,0.8856921,0.0004280358],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8419286,0.0001585116,0.009916267,0.000134563,0.001348347,0.00002112918,0.000003186143,0.0005673347,0.145922],"genre_scores_gemma":[0.9910583,0.00003685998,0.005101562,0.00008169167,0.000310429,0.00001412388,0.00001758952,0.00002836068,0.003351062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8229395,"threshold_uncertainty_score":0.394133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004905304267018387,"score_gpt":0.1976159567397076,"score_spread":0.1927106524726892,"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."}}