{"id":"W3006410912","doi":"10.33322/energi.v11i2.765","title":"Pengembangan kWh Meter Elektronik untuk Pengecekan CT Konsumen Secara On Site","year":2019,"lang":"en","type":"article","venue":"Energi & Kelistrikan","topic":"Engineering and Technology Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Positive Living North","funders":"","keywords":"Procurement; Duration (music); Metre; Revenue; Computer science; Business; Marketing; Finance","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":[0.0007502378,0.0007205774,0.0005112182,0.0008440377,0.0005591582,0.002004933,0.0006655076,0.0008037454,0.02795599],"category_scores_gemma":[0.001572625,0.0004353452,0.0003012384,0.000841157,0.00056628,0.002515119,0.0008404655,0.001123768,0.01015696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005539408,"about_ca_system_score_gemma":0.0008342731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001556637,"about_ca_topic_score_gemma":0.001950574,"domain_scores_codex":[0.9993498,0.0000794255,0.00003842019,0.0001086678,0.0003665065,0.00005717488],"domain_scores_gemma":[0.9989282,0.0002829501,0.00007855772,0.0001472369,0.000501113,0.00006181581],"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":[0.0009523173,0.0001537656,0.01225761,0.001323547,0.00005954425,0.002058513,0.0008323819,0.005764389,0.1169476,0.01182374,0.03571316,0.8121135],"study_design_scores_gemma":[0.0001432303,0.0006787789,0.03334467,0.0005265626,0.0002203107,0.009118221,0.002335163,0.02376864,0.2676123,0.01346,0.6484473,0.0003446842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2393973,0.01323286,0.374598,0.004903122,0.002824883,0.0005260525,0.002844966,0.009565813,0.352107],"genre_scores_gemma":[0.770327,0.004807122,0.09441492,0.0006793045,0.0003491815,0.0001608153,0.001743531,0.001364066,0.1261541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02795599,"threshold_uncertainty_score":0.09352207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004157169754226721,"score_gpt":0.1805275149692972,"score_spread":0.1763703452150704,"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."}}