{"id":"W3107372481","doi":"","title":"FUZZY LOGIC MAMDANI PENERIMAAN SEMBAKO UNTUK KELUARGA MISKIN","year":2020,"lang":"id","type":"article","venue":"","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Government (linguistics); Poverty; Economics; Agriculture; Economic growth; Business; Public economics; Development economics; Geography","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":[0.0003484273,0.0005271492,0.0006778596,0.0004110207,0.0006972675,0.001643298,0.000346979,0.0007503147,0.005787255],"category_scores_gemma":[0.0005973243,0.0001857911,0.0004932988,0.000403164,0.0004913407,0.0006662428,0.0003732384,0.0008975976,0.001132663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007576629,"about_ca_system_score_gemma":0.000945938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004706507,"about_ca_topic_score_gemma":0.003714604,"domain_scores_codex":[0.9998109,0.00005438158,0.0000148751,0.00003898303,0.00006339372,0.00001744941],"domain_scores_gemma":[0.9998564,0.00005659303,0.00001260484,0.000005645441,0.00006219472,0.000006494895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005236359,0.0001707865,0.003723841,0.001311286,0.0001951,0.001735919,0.000985358,0.2942494,0.02601528,0.1862938,0.01743525,0.4673604],"study_design_scores_gemma":[0.00005227423,0.0003256374,0.003599486,0.0004797463,0.0001260269,0.001109763,0.0005903587,0.8557116,0.01129947,0.05984291,0.06674785,0.0001148845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08537956,0.02357306,0.7441353,0.004513757,0.00150068,0.0002159523,0.0005152466,0.0007687837,0.1393977],"genre_scores_gemma":[0.8255634,0.01219927,0.1037232,0.0004617714,0.0002406391,0.0002166776,0.0003579427,0.00004779867,0.05718937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005787255,"threshold_uncertainty_score":0.0193603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04539324620796208,"score_gpt":0.2594598196717026,"score_spread":0.2140665734637405,"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."}}