{"id":"W4409646061","doi":"10.2139/ssrn.5222406","title":"Fault Diagnosis in Photovoltaic Systems Using Machine Learning Algorithms","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"West African Science Service Centre on Climate Change and Adapted Land Use; International Development Research Centre","keywords":"Photovoltaic system; Computer science; Fault (geology); Algorithm; Machine learning; Artificial intelligence; Engineering; Electrical engineering; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0008024112,0.0007819426,0.0007759591,0.001065619,0.0003845845,0.0008522576,0.0005131963,0.0007656836,0.0009695284],"category_scores_gemma":[0.003421183,0.000318193,0.000531795,0.0007054257,0.0003004754,0.0007108773,0.0003707397,0.0008213127,0.0002486434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006815711,"about_ca_system_score_gemma":0.00062538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005115578,"about_ca_topic_score_gemma":0.003938173,"domain_scores_codex":[0.9996603,0.0001104642,0.00003409967,0.00007447925,0.00008705846,0.00003365483],"domain_scores_gemma":[0.9986513,0.0009433027,0.0001373175,0.00006476458,0.0001859927,0.00001740364],"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":[0.00003141349,0.00002646263,0.001183762,0.00004850041,0.00003116897,0.00004275573,0.00002097971,0.9367362,0.000872476,0.0008283965,0.0002545902,0.05992334],"study_design_scores_gemma":[0.000001618566,0.000008399294,0.0002207377,0.000005029731,0.000002421875,0.00001121703,0.000003861261,0.9985294,0.0003634513,0.0007595588,0.00009222291,0.000001949825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06992896,0.001108303,0.9241251,0.0003056969,0.00005740803,0.00005885534,0.00009989315,0.001427663,0.002888126],"genre_scores_gemma":[0.8691527,0.0003762314,0.128989,0.00005912393,0.00003533456,0.00007704915,0.0001614612,0.0000471155,0.001101985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005115578,"threshold_uncertainty_score":0.01017159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794566915657625,"score_gpt":0.276868178162322,"score_spread":0.2589225090057458,"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."}}