{"id":"W2958501180","doi":"10.25077/jmu.8.2.84-92.2019","title":"PERAMALAN BEBAN LISTRIK JANGKA MENENGAH DI WILAYAH TELUK KUANTAN DENGAN METODE FUZZY TIME SERIES CHENG","year":2019,"lang":"id","type":"article","venue":"Jurnal Matematika UNAND","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Mathematics","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","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00271061,0.001125774,0.001837908,0.0004813391,0.000719541,0.00227957,0.002498438,0.0005911747,0.0005433989],"category_scores_gemma":[0.0004130597,0.0009972589,0.0004605328,0.0009650769,0.000200368,0.002025599,0.0008116246,0.001541644,0.00894726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004091064,"about_ca_system_score_gemma":0.0004739707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002262355,"about_ca_topic_score_gemma":0.00003343417,"domain_scores_codex":[0.9917302,0.001432199,0.001891304,0.001491108,0.001867409,0.00158779],"domain_scores_gemma":[0.9946164,0.0007087071,0.001404492,0.002065936,0.0004327604,0.0007716323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001207425,0.00270708,0.3354432,0.02776372,0.005014902,0.002785653,0.1172956,0.005155316,0.433571,0.02962861,0.02921095,0.01021656],"study_design_scores_gemma":[0.01848208,0.006922035,0.304328,0.02842003,0.001809636,0.008850383,0.007690807,0.3722456,0.103733,0.001329351,0.1315079,0.01468104],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769272,0.00200349,0.0007095113,0.00141423,0.004166805,0.001829732,0.00006287279,0.0005226544,0.01236354],"genre_scores_gemma":[0.9496558,0.0001353389,0.002298224,0.0001833706,0.0008746265,0.00005738735,0.00004262337,0.0001730851,0.04657952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670903,"threshold_uncertainty_score":0.9992478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009094762381076746,"score_gpt":0.2268168415286901,"score_spread":0.2177220791476134,"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."}}