{"id":"W1991650290","doi":"10.1007/978-3-642-38171-3_19","title":"Solving Wind Farm Layout Optimization with Mixed Integer Programming and Constraint Programming","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematical optimization; Computer science; Nonlinear programming; Wind power; Integer programming; Constraint programming; Stochastic programming; Constraint (computer-aided design); Aerodynamics; Nonlinear system; Linear programming; Integer (computer science); Algorithm; Mathematics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003004816,0.0003721709,0.0003033619,0.0003919352,0.0001417256,0.0005674106,0.0003339891,0.0001891321,0.00003221748],"category_scores_gemma":[0.00002396592,0.0002994802,0.00003031751,0.0002239778,0.0005595823,0.0002175113,0.0002081389,0.0005551581,0.000005657665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001896272,"about_ca_system_score_gemma":0.0001866866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001916384,"about_ca_topic_score_gemma":0.00008506114,"domain_scores_codex":[0.9980539,0.000009114383,0.0002684044,0.0005622236,0.0004901484,0.0006162033],"domain_scores_gemma":[0.9992509,0.00008601938,0.00005730484,0.0002515473,0.0001607591,0.0001934939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000222025,0.000004001347,0.00003641254,0.00005168789,0.00001453705,0.00002141772,0.0003653625,0.4858686,0.00001464901,0.0001650981,0.000002287272,0.5134537],"study_design_scores_gemma":[0.0002991388,0.0001381074,0.00005154952,0.000830544,0.000008665485,0.0000999475,0.000004503143,0.994823,0.0003700661,0.0007169578,0.002011843,0.0006456451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006292451,0.0003017775,0.9959833,0.00006463823,0.0002750472,0.0004461756,0.000001174246,0.0001814716,0.002117143],"genre_scores_gemma":[0.2338721,0.00003811928,0.7655926,0.0000585609,0.0001780419,0.00002637148,0.00001493372,0.00006079098,0.0001585073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5128081,"threshold_uncertainty_score":0.9999458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01014855123956549,"score_gpt":0.2058750280905522,"score_spread":0.1957264768509867,"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."}}