{"id":"W2035103704","doi":"10.2316/journal.201.2004.1.201-1171","title":"An Advanced Model for Short-Term Forecasting of Mean Wind Speed and Wind Electric Power","year":2004,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Term (time); Wind speed; Wind power; Meteorology; Environmental science; Wind power forecasting; Power (physics); Computer science; Electric power system; Engineering; Electrical engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002129627,0.000212429,0.0003741155,0.0001092122,0.00007199942,0.00004869808,0.00008879849,0.00009427942,0.000001317617],"category_scores_gemma":[0.00002108186,0.0001920483,0.00005900433,0.00007832386,0.00002667857,0.0001828563,0.000008814836,0.0000922324,4.055525e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003662139,"about_ca_system_score_gemma":0.00001501924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001439387,"about_ca_topic_score_gemma":0.000009499297,"domain_scores_codex":[0.9988894,0.00001272989,0.0004506516,0.0002231848,0.0001073818,0.000316612],"domain_scores_gemma":[0.9995196,0.00006381111,0.00006557399,0.0001478124,0.00007036688,0.0001327995],"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":[0.00005920833,0.00002095118,0.0004288142,0.0002495451,0.00007358311,0.000002013606,0.001110903,0.9365877,0.05079286,0.0007988872,0.000004134311,0.0098714],"study_design_scores_gemma":[0.0008622261,0.0002272197,0.00005207049,0.0002492442,0.00003843305,0.00002686489,0.0001754366,0.9935519,0.004346565,0.0001236459,0.0001205933,0.0002258672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913116,0.004497721,0.08101965,0.000004941541,0.0003748233,0.000274856,0.00002400119,0.00007407984,0.0006139753],"genre_scores_gemma":[0.9993884,0.0001259257,0.0002415205,0.00001024546,0.0001044896,0.000005942958,0.000008550815,0.00004146668,0.00007348722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08627241,"threshold_uncertainty_score":0.7831503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033662579337544,"score_gpt":0.2300696917380349,"score_spread":0.2097330659446595,"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."}}