{"id":"W2059605169","doi":"10.1109/tste.2015.2403845","title":"An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Maximum power point tracking; Photovoltaic system; Maximum power principle; Voltage; Control theory (sociology); Computer science; Electronic engineering; Power (physics); Noise (video); Algorithm; Engineering; Electrical engineering; Inverter; Artificial intelligence; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006866843,0.0004418222,0.0005080235,0.0005795529,0.0003464367,0.0003362479,0.0003143986,0.0002580718,0.00003839067],"category_scores_gemma":[0.00002536988,0.0004111599,0.0001392902,0.0006288639,0.0000889459,0.00122704,0.00000219178,0.000172771,0.000007807045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008910371,"about_ca_system_score_gemma":0.0002824049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003293056,"about_ca_topic_score_gemma":0.00004976653,"domain_scores_codex":[0.9971905,0.0002205305,0.0006519543,0.0006091628,0.0005541393,0.000773738],"domain_scores_gemma":[0.9975129,0.0001787107,0.0002782052,0.0007287062,0.0009425331,0.0003589282],"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":[0.0002494309,0.0002921973,5.662351e-7,0.00007887591,0.0001026248,0.00003516623,0.0005339294,0.9764894,0.00009273872,0.002594835,0.0002257669,0.01930444],"study_design_scores_gemma":[0.001603553,0.001630876,6.952559e-7,0.000101018,0.0001080217,0.0001072277,0.009295265,0.9380451,0.04483362,0.001027558,0.002677807,0.0005692872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001955098,0.0000541823,0.9942988,0.00004917257,0.0004078062,0.0009079618,0.00003028861,0.0009357249,0.001361022],"genre_scores_gemma":[0.8359812,0.00000995031,0.1601642,0.0001103769,0.00003887241,0.001763219,0.00005365265,0.0001525839,0.001725962],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8341346,"threshold_uncertainty_score":0.999834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173984134166837,"score_gpt":0.2550071060257386,"score_spread":0.2376086926090549,"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."}}