{"id":"W1593740443","doi":"10.1109/naps.2005.1560560","title":"A V-I slope-based method for flicker source detection","year":2005,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Flicker; Luminance; Computer science; Troubleshooting; Power quality; Flicker noise; Schematic; Impression; Computer vision; Artificial intelligence; Voltage; Electronic engineering; Engineering; Telecommunications; Electrical engineering; Bandwidth (computing); 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":[0.0003686752,0.0008299581,0.0005134715,0.002054124,0.0003636218,0.0007918121,0.0009776317,0.0009131556,0.00419847],"category_scores_gemma":[0.001530983,0.0003136467,0.0003271508,0.00142811,0.0003129367,0.0006405108,0.0004232306,0.0007922764,0.002851471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276917,"about_ca_system_score_gemma":0.0002834166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000896091,"about_ca_topic_score_gemma":0.001552803,"domain_scores_codex":[0.9993947,0.00009228822,0.00002679347,0.0001334227,0.0003193561,0.00003343382],"domain_scores_gemma":[0.9994826,0.0001060481,0.00006579052,0.00007576214,0.0002457635,0.00002393447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003040559,0.0001220874,0.003144989,0.0005419703,0.00006058369,0.0002972482,0.0002328378,0.00437165,0.3406819,0.004492731,0.004990914,0.6407591],"study_design_scores_gemma":[0.0001291116,0.001729805,0.02365871,0.0002864361,0.0002178703,0.007391619,0.0004526231,0.499901,0.3823882,0.006939752,0.07647003,0.0004349572],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009969409,0.0005706621,0.9761678,0.00007824929,0.0001629949,0.0001725511,0.0001724242,0.004287738,0.008418265],"genre_scores_gemma":[0.4248041,0.0009447994,0.5634494,0.0001985997,0.0001234947,0.0002766942,0.0003888866,0.0003951132,0.009418868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00419847,"threshold_uncertainty_score":0.01404524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02405381019224247,"score_gpt":0.2774613055555598,"score_spread":0.2534074953633173,"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."}}