{"id":"W4409858418","doi":"10.18280/jesa.580314","title":"Prediction Efficiency and Sustainability of a Photovoltaic System in the Steppe Area of M'sila, Algeria, Using Machine Learning","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Photovoltaic system; Sustainability; Steppe; Environmental science; Computer science; Environmental economics; Engineering; Geography; Economics; Electrical engineering; Ecology; Biology; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002006153,0.0002778711,0.0002713344,0.0004406014,0.0003061905,0.0004920803,0.0002831684,0.0005028577,0.0005817891],"category_scores_gemma":[0.0003497521,0.000114867,0.0003339314,0.0004052157,0.0001813669,0.0002848668,0.0001991066,0.0002074591,0.0001166601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000893249,"about_ca_system_score_gemma":0.0004200517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07013017,"about_ca_topic_score_gemma":0.0771075,"domain_scores_codex":[0.9999079,0.00002428777,0.000006751504,0.00001926629,0.0000204143,0.00002142934],"domain_scores_gemma":[0.9998419,0.00007450778,0.00002105815,0.00000691835,0.00004347708,0.00001204924],"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":[0.0003755807,0.0004439384,0.4583121,0.0001433398,0.0003912347,0.0009938007,0.0002890448,0.4879368,0.0112384,0.0006528836,0.00118109,0.03804171],"study_design_scores_gemma":[0.00002297747,0.0001217143,0.461313,0.00001101881,0.00006609465,0.00009842938,0.0005183097,0.5345398,0.00252025,0.0002801074,0.0004908626,0.00001741826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987577,0.000029308,0.0005207821,0.00004005531,0.000002337024,0.000004881098,0.0001451135,0.00002273532,0.000477],"genre_scores_gemma":[0.9993394,0.00001783823,0.0002604031,0.000003568536,0.000001280349,0.000002985157,0.0001085257,0.000001767288,0.000264055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07013017,"threshold_uncertainty_score":0.1394439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248139840617173,"score_gpt":0.2300012216513843,"score_spread":0.2175198232452126,"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."}}