{"id":"W1899446485","doi":"10.1016/j.renene.2015.06.026","title":"The impact of land use constraints in multi-objective energy-noise wind farm layout optimization","year":2015,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Hatch (Canada); University of Toronto","funders":"","keywords":"Wind power; Constraint (computer-aided design); Noise (video); Mathematical optimization; Computer science; Wind speed; Land use; Variable (mathematics); Environmental science; Civil engineering; Meteorology; Engineering; Geography; Mathematics","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":[0.0002106901,0.0001740197,0.0002050805,0.0001574036,0.00004749343,0.00005940656,0.0001598035,0.0001000848,0.00002012251],"category_scores_gemma":[0.0001154765,0.0001253743,0.00006277015,0.0003539819,0.0000841143,0.0001506619,0.00004965998,0.00007342082,0.000001380075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002877435,"about_ca_system_score_gemma":0.0002685077,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03254598,"about_ca_topic_score_gemma":0.006829354,"domain_scores_codex":[0.9988655,0.00007050796,0.00026106,0.0001609054,0.0002323703,0.000409666],"domain_scores_gemma":[0.9993079,0.000105194,0.00004073988,0.000219279,0.0001243628,0.0002025722],"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":[0.00004864058,0.00003914153,0.00509904,0.000003368596,0.00007672938,0.0000105827,0.0001348027,0.9916586,0.0005003837,0.00006829597,0.000509094,0.001851346],"study_design_scores_gemma":[0.001780386,0.00009736623,0.005255972,0.00004793903,0.000005619965,0.00001080558,0.0001861592,0.9791971,0.01098869,0.0001778388,0.001967904,0.0002842625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5644704,0.003506528,0.3822114,0.00004895304,0.0009032838,0.0003227494,0.0001138997,0.0004432506,0.04797957],"genre_scores_gemma":[0.9966369,0.0004254256,0.00151559,0.00000757575,0.00004165701,0.00001749761,0.00004428218,0.00003157427,0.001279486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4321665,"threshold_uncertainty_score":0.9738964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02593267886976117,"score_gpt":0.2532573393843768,"score_spread":0.2273246605146157,"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."}}