{"id":"W1628560151","doi":"10.1109/pesgm.2015.7285745","title":"Online clustering modeling of large-scale photovoltaic power plants","year":2015,"lang":"en","type":"article","venue":"","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cluster analysis; Photovoltaic system; Computer science; Sensitivity (control systems); Data mining; Maximum power point tracking; Scale (ratio); Matching (statistics); Feature (linguistics); Power (physics); Inverter; Artificial intelligence; Electronic engineering; Engineering; Mathematics; Voltage; Statistics; Electrical engineering","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":[0.0002618883,0.0004906967,0.0005171132,0.0003267014,0.0003891735,0.0005542329,0.001038828,0.0005269651,0.001204466],"category_scores_gemma":[0.0006830882,0.0003306842,0.0005668906,0.0003881425,0.0002838033,0.0009848722,0.0004298114,0.0005537827,0.0002904448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007176871,"about_ca_system_score_gemma":0.0004601339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007833255,"about_ca_topic_score_gemma":0.006003588,"domain_scores_codex":[0.9997899,0.0000428409,0.000008778634,0.00006009133,0.00007692471,0.00002145509],"domain_scores_gemma":[0.9997657,0.0000796095,0.00004331457,0.00003102059,0.00006864745,0.00001179709],"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":[0.000008914033,0.000008140265,0.000179564,0.00001046589,0.000006592804,0.00002383654,0.00001535607,0.9894279,0.001423307,0.001212923,0.0001478314,0.007535102],"study_design_scores_gemma":[4.476467e-7,0.000002377145,0.00006025452,4.121784e-7,7.41257e-7,0.000003950071,0.00000172921,0.9993415,0.0002042204,0.0003101662,0.00007265968,0.000001469091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03366557,0.00008723701,0.9617411,0.00007179925,0.00001645859,0.00003007166,0.00005875137,0.0005041133,0.003825006],"genre_scores_gemma":[0.9513891,0.0001225869,0.04517784,0.00002498048,0.00001185292,0.00006839846,0.0001047576,0.0000880901,0.003012276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007833255,"threshold_uncertainty_score":0.01557529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343820303595343,"score_gpt":0.2791569607335846,"score_spread":0.2447749303740503,"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."}}