{"id":"W7139949961","doi":"10.1109/isgtasia63446.2025.11431299","title":"A Hybrid Wind Power Forecasting System Integrating Dynamic Model Selection and Data Augmentation","year":2025,"lang":"","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Selection (genetic algorithm); Wind power; Model selection; Power (physics); Feature selection; Data modeling","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":[0.0006659578,0.0004804604,0.0004166629,0.0003653445,0.0004814432,0.0004061462,0.0003538108,0.0001635533,0.00003290703],"category_scores_gemma":[0.0001400889,0.0005072919,0.00006039835,0.0004722633,0.00003650074,0.001016338,0.000407402,0.0004940075,0.000005085572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004785506,"about_ca_system_score_gemma":0.0001312755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001999991,"about_ca_topic_score_gemma":0.0002971654,"domain_scores_codex":[0.9974686,0.00006610584,0.0008440018,0.000819847,0.0002244069,0.0005770305],"domain_scores_gemma":[0.9989204,0.0001846839,0.0001599799,0.0005100485,0.0001095747,0.0001152795],"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":[0.00004231629,0.00003165171,0.0005042532,0.00152851,0.0003372323,0.00001113483,0.0009056094,0.9148857,0.004860068,0.01158967,0.0003984873,0.06490535],"study_design_scores_gemma":[0.0005952351,0.00004469034,0.0000400225,0.002199983,0.0001724052,0.00009389016,0.001373527,0.9939566,0.0008008357,0.0001946164,0.0001106897,0.0004175263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3295027,0.0009654282,0.6291177,0.00005176443,0.001118189,0.0003165154,0.00007761046,0.0004261017,0.03842394],"genre_scores_gemma":[0.9767782,0.00005338412,0.02152544,0.00003883298,0.00006400694,0.000009317807,0.0001830133,0.00006576259,0.001282006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6472755,"threshold_uncertainty_score":0.9997379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952250475346263,"score_gpt":0.2528162692923844,"score_spread":0.2332937645389218,"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."}}