{"id":"W4408675662","doi":"10.5194/wes-2025-29","title":"Minimum Open Data Subset for Wind Power Prediction","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wind power; Open data; Power (physics); Predictive power; Computer science; Meteorology; Environmental science; Geography; Physics; Electrical engineering; Engineering; Philosophy; World Wide Web; Epistemology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001797206,0.0009561764,0.0009325739,0.0008858151,0.0005600143,0.0008065242,0.00138053,0.0006042312,0.003058472],"category_scores_gemma":[0.007383988,0.0004106189,0.001160673,0.001267799,0.0002468814,0.001311914,0.0008354902,0.0008823877,0.00118421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005972155,"about_ca_system_score_gemma":0.001530816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04405536,"about_ca_topic_score_gemma":0.03842504,"domain_scores_codex":[0.9991086,0.0002331746,0.00006666957,0.0002077842,0.0002997495,0.00008398514],"domain_scores_gemma":[0.9972196,0.0009586613,0.0001611924,0.0006877671,0.0008609223,0.0001119496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001941664,0.0006612792,0.04889688,0.0005104656,0.0005175359,0.0004124931,0.0001308074,0.6568397,0.004588629,0.003243716,0.07379555,0.2084613],"study_design_scores_gemma":[0.00006841096,0.00006684419,0.01103171,0.00004225576,0.00003559452,0.00005318287,0.00004632158,0.9766765,0.002441393,0.002468672,0.007048217,0.00002097041],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4887717,0.001814749,0.3265995,0.0009376247,0.0005744143,0.0007760254,0.1587539,0.01212386,0.009648204],"genre_scores_gemma":[0.6572166,0.0002718009,0.1076422,0.00009850353,0.00007656414,0.000566418,0.2316463,0.0004518876,0.00202971],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9986195,"threshold_uncertainty_score":0.08759785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05854305630025496,"score_gpt":0.2928459621540143,"score_spread":0.2343029058537593,"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."}}