{"id":"W4415368043","doi":"10.1109/sege65970.2025.11203747","title":"Advanced and Optimized Forecasting Techniques for Wind Power Generation: A Comparative Analysis","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":"University of New Brunswick","funders":"","keywords":"Boosting (machine learning); Wind power; Stability (learning theory); Renewable energy; Time horizon; Gradient boosting; Point (geometry); Event (particle physics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003592889,0.0004728447,0.000926764,0.0006281985,0.0004043218,0.0002423481,0.000152862,0.0002271486,0.0001894301],"category_scores_gemma":[0.00008106391,0.0004773882,0.0003197606,0.001361373,0.00008407449,0.0003489256,0.00009559888,0.0002146562,9.181543e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009330575,"about_ca_system_score_gemma":0.00005458984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002045605,"about_ca_topic_score_gemma":0.00009413029,"domain_scores_codex":[0.9979646,0.00005012923,0.0007540465,0.0005894064,0.0001335494,0.0005082494],"domain_scores_gemma":[0.9987932,0.0004183361,0.0001333564,0.0003009696,0.0002355423,0.0001186047],"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":[0.0002506925,0.00008667219,0.0004557303,0.0002395353,0.005905155,0.000005547793,0.002800064,0.9105256,0.008789154,0.03017335,0.001702783,0.03906572],"study_design_scores_gemma":[0.00115088,0.0001361625,0.00004936463,0.0001854706,0.001176305,0.000002945689,0.0004740361,0.9470428,0.03721414,0.0001835404,0.01187721,0.0005071358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05999346,0.00340913,0.8395172,0.0001860543,0.0005723237,0.0009151834,0.00005348089,0.0003392696,0.09501393],"genre_scores_gemma":[0.7532411,0.0001182195,0.2437196,0.0001086449,0.000113893,0.00008968719,0.00005893809,0.00002190804,0.002528087],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6932476,"threshold_uncertainty_score":0.9997678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0305753242430447,"score_gpt":0.2824461845654454,"score_spread":0.2518708603224007,"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."}}