{"id":"W4408609386","doi":"10.1109/access.2025.3552733","title":"Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Wavelet packet decomposition; Hilbert–Huang transform; Computer science; Shading; Wavelet transform; Discrete wavelet transform; Decomposition; Wavelet; Second-generation wavelet transform; Mode (computer interface); Network packet; Artificial intelligence; Computer vision; Computer network; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002750968,0.0002890079,0.0002486622,0.0004024572,0.0001070734,0.0002695758,0.0001285671,0.0002060331,0.0003776883],"category_scores_gemma":[0.0006253195,0.0001298057,0.0003306198,0.0006246534,0.0001141339,0.0003985969,0.0001797769,0.000284278,0.0001065088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007834639,"about_ca_system_score_gemma":0.0001794046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008473877,"about_ca_topic_score_gemma":0.0007776243,"domain_scores_codex":[0.9998971,0.00001780853,0.00000632199,0.00001637301,0.00005234483,0.00000999009],"domain_scores_gemma":[0.9998912,0.00004685979,0.00001727166,0.00001018787,0.00003138062,0.000003087877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007025131,0.00007582435,0.004850836,0.0001710634,0.00006922854,0.0001736195,0.0001173664,0.2397165,0.07262026,0.003590084,0.0007142599,0.6778307],"study_design_scores_gemma":[0.00000335027,0.00005449953,0.005105988,0.000008015035,0.0000117765,0.00008295799,0.00002841468,0.985801,0.006820012,0.001265317,0.0008106089,0.000007945611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08356699,0.0002276728,0.9150605,0.0000548123,0.00001785034,0.00001660086,0.000041156,0.0001492856,0.000865179],"genre_scores_gemma":[0.740657,0.0009065872,0.2566905,0.00002502685,0.00002743825,0.00004427829,0.0002138814,0.00004000634,0.001395307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008473877,"threshold_uncertainty_score":0.001684904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04259379601973379,"score_gpt":0.4191168577821551,"score_spread":0.3765230617624213,"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."}}