{"id":"W1981481872","doi":"10.1049/iet-rpg.2009.0137","title":"Multiple model multiple-input multiple-output predictive control for variable speed variable pitch wind energy conversion systems","year":2011,"lang":"en","type":"article","venue":"IET Renewable Power Generation","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Control theory (sociology); Torque; Wind power; Controller (irrigation); Multivariable calculus; Model predictive control; Wind speed; Actuator; Power (physics); Generator (circuit theory); Computer science; Variable (mathematics); Pitch control; Operating point; Engineering; Control engineering; Control (management); Mathematics; Electronic 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007264232,0.0007243136,0.0009051955,0.0002992117,0.0003454447,0.000213193,0.0004343475,0.0006226609,0.0000514557],"category_scores_gemma":[0.0003255962,0.0007478776,0.0002135185,0.0003448086,0.00005059383,0.0008674925,0.00006068841,0.0002189472,0.00002899281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004060989,"about_ca_system_score_gemma":0.0002036858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004276107,"about_ca_topic_score_gemma":0.0002433256,"domain_scores_codex":[0.9962953,0.0001705444,0.001074707,0.0008966607,0.0005346204,0.001028179],"domain_scores_gemma":[0.9974428,0.0003861227,0.0002969775,0.0008768652,0.0006449393,0.0003523387],"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":[0.000322803,0.0001148476,0.001776532,0.0001167219,0.0003314547,0.000003298708,0.0004194606,0.8011005,0.1841205,0.0004804988,0.01119502,0.00001836967],"study_design_scores_gemma":[0.008290624,0.0002490738,0.00008544521,0.00009294239,0.0001746198,0.00001413908,0.0001133085,0.9533327,0.02675906,0.0001127612,0.01002632,0.0007490534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02084772,0.0008792665,0.9653924,0.0000172505,0.004689327,0.00224235,0.0006949557,0.0007942018,0.004442595],"genre_scores_gemma":[0.9847815,0.00002501236,0.009411483,0.0001013015,0.001194194,0.0003976959,0.0005758318,0.0002248259,0.003288146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9639338,"threshold_uncertainty_score":0.9994972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966143619945406,"score_gpt":0.1902931751529323,"score_spread":0.1706317389534782,"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."}}