{"id":"W4408540338","doi":"10.1109/tim.2025.3551857","title":"Improved Butterfly Optimization Algorithm for Parameter Identification of Various Photovoltaic Models Including Power Station","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Scientific Research Fund of Liaoning Provincial Education Department","keywords":"Photovoltaic system; Computer science; Identification (biology); Optimization algorithm; Algorithm; Power (physics); Engineering; Electrical engineering; Mathematical optimization; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004424567,0.0008582597,0.0005728468,0.0005333196,0.0004238258,0.0004949709,0.0006959146,0.0007628436,0.002005511],"category_scores_gemma":[0.001128059,0.0003153924,0.0007346873,0.000441646,0.0002908561,0.00057556,0.0005327061,0.0007664973,0.0003865705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004558379,"about_ca_system_score_gemma":0.0009614514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107419,"about_ca_topic_score_gemma":0.01117218,"domain_scores_codex":[0.9998386,0.00003471156,0.00001190135,0.0000397577,0.00005320564,0.00002178098],"domain_scores_gemma":[0.9997224,0.0001345507,0.00003471594,0.00002158063,0.00007796559,0.00000880048],"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":[0.00003963739,0.0000284446,0.001272622,0.00006469037,0.00004394582,0.00003940319,0.00006042401,0.9055008,0.003718074,0.002649185,0.001077018,0.08550574],"study_design_scores_gemma":[0.000003872741,0.00001118487,0.0001245368,0.000003623239,0.000003980253,0.000008916368,0.000005091043,0.9985369,0.0004665785,0.0004533398,0.0003789353,0.00000308634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02335774,0.0002505724,0.9726582,0.0001083376,0.00002357243,0.00003861653,0.00005539312,0.0005173693,0.00299025],"genre_scores_gemma":[0.6196269,0.0002924283,0.3738112,0.0001927221,0.00002868,0.0003086129,0.0003797329,0.0001527367,0.005207028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01107419,"threshold_uncertainty_score":0.02201945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218388742340388,"score_gpt":0.262783118413971,"score_spread":0.2305992309905671,"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."}}