{"id":"W4411070469","doi":"10.3390/en18112975","title":"Ensemble of Artificial Neural Networks for Seasonal Forecasting of Wind Speed in Eastern Canada","year":2025,"lang":"en","type":"article","venue":"Energies","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Artificial neural network; Meteorology; Wind speed; Climatology; Artificial intelligence; Environmental science; Computer science; Geography; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0008115206,0.0006320107,0.0005486301,0.0005774072,0.0006683175,0.0006664597,0.0007981224,0.0002781293,0.0005400991],"category_scores_gemma":[0.001434162,0.0002108804,0.0004410725,0.0007988285,0.0001351222,0.0003577293,0.0004203792,0.0005532314,0.000115517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002432702,"about_ca_system_score_gemma":0.003434015,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7283427,"about_ca_topic_score_gemma":0.7263005,"domain_scores_codex":[0.9998081,0.00002479295,0.00001428096,0.00004031838,0.00005711438,0.00005539845],"domain_scores_gemma":[0.9995695,0.0000731094,0.00002951792,0.00003094593,0.0002629732,0.00003392208],"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":[0.00012246,0.00007864939,0.02805885,0.00002406626,0.000138714,0.00007314685,0.00004511779,0.9167606,0.0008835468,0.0002445543,0.001245788,0.05232445],"study_design_scores_gemma":[0.000002581043,0.000008039805,0.005927036,0.00000246875,0.00001426989,0.000002878801,0.00001926314,0.9934319,0.0003453199,0.0000477114,0.0001935595,0.000005000757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805042,0.0004297295,0.01523229,0.0001402208,0.00007193537,0.00002955101,0.000789732,0.0002594476,0.002542922],"genre_scores_gemma":[0.9936241,0.0001418351,0.004287413,0.00001019967,0.00000909962,0.00001000422,0.0008683945,0.00001023554,0.001038726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2716573,"threshold_uncertainty_score":0.5465144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01691724206370419,"score_gpt":0.2129449475703652,"score_spread":0.196027705506661,"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."}}