{"id":"W4319429859","doi":"10.24843/spektrum.2020.v07.i01.p15","title":"PENGGUNAAN KAPASITOR BANK UNTUK MEMPERBAIKI FAKTOR DAYA DAN MENGURANGI RUGI-RUGI DAYA MENGGUNAKAN FUZZY LOGIC CONTROLLER DI QUEST HOTEL KUTA BADUNG","year":2020,"lang":"en","type":"article","venue":"Jurnal SPEKTRUM","topic":"Engineering and Technology Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Power factor; Capacitor; AC power; Fuzzy logic; Electrical engineering; Controller (irrigation); Power (physics); Physics; Computer science; Engineering; Artificial intelligence; Voltage","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":[0.0002564556,0.0006621637,0.0007647393,0.0003127597,0.0002893319,0.0001546888,0.0007583986,0.0004653055,0.0001564637],"category_scores_gemma":[0.0001808983,0.0006470212,0.0002533363,0.0009624393,0.0001318533,0.0003400253,0.0001360552,0.001360568,0.0002379245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002103244,"about_ca_system_score_gemma":0.00004944118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002464646,"about_ca_topic_score_gemma":0.00001941111,"domain_scores_codex":[0.99715,0.00005069776,0.0008034326,0.000585232,0.0004604425,0.0009501779],"domain_scores_gemma":[0.998676,0.0001139971,0.0001307675,0.0005585839,0.0001248116,0.0003958307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004436872,0.0007662021,0.0384767,0.001466895,0.005027452,0.00142472,0.005638097,0.1118466,0.5151375,0.2308484,0.06903537,0.01988835],"study_design_scores_gemma":[0.01864924,0.002323384,0.1347912,0.0008559878,0.001515546,0.0007456577,0.002708075,0.1958702,0.08644379,0.005624957,0.5410705,0.00940147],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9298348,0.003523018,0.009907084,0.01223987,0.003929489,0.001191286,0.0002895356,0.006623938,0.03246101],"genre_scores_gemma":[0.9962254,0.0001957314,0.001178569,0.000501568,0.001367562,0.00006102494,0.00006969021,0.0001708086,0.0002296274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4720352,"threshold_uncertainty_score":0.9995981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020839350080703,"score_gpt":0.2041372724621729,"score_spread":0.1939288789613659,"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."}}