{"id":"W4366420847","doi":"10.36595/jire.v6i1.726","title":"ALGORITMA APRIORI UNTUK MENENTUKAN PAKET PENJUALAN BARANG DI UMKM BINAAN DISPERINDAG KABUPATEN GROBOGAN","year":2023,"lang":"id","type":"article","venue":"Jurnal Informatika dan Rekayasa Elektronik","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Humanities; Physics; Computer science; Art","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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002013557,0.001108154,0.001098801,0.001025066,0.001805075,0.002266708,0.004089484,0.0004373468,0.0001384919],"category_scores_gemma":[0.0002937691,0.001074636,0.0005073277,0.003114055,0.0003631568,0.003373995,0.002169933,0.002099586,0.006508608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004371772,"about_ca_system_score_gemma":0.0006829053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005636141,"about_ca_topic_score_gemma":0.00007685016,"domain_scores_codex":[0.9923571,0.0003649613,0.002036989,0.00118683,0.001635058,0.002419074],"domain_scores_gemma":[0.9943247,0.0004434828,0.001145082,0.002715311,0.0003019331,0.001069424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002174502,0.0009239095,0.0364015,0.001293973,0.001262553,0.0005555728,0.05161433,0.004522443,0.001649858,0.06560063,0.146208,0.6897498],"study_design_scores_gemma":[0.002595809,0.0009845498,0.1277518,0.0005548757,0.0002177588,0.0004539985,0.003144127,0.2181691,0.0005236128,0.0003481466,0.6430357,0.002220512],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8570046,0.001230492,0.05242497,0.01812872,0.006739209,0.003240895,0.001384068,0.006038641,0.05380842],"genre_scores_gemma":[0.9739618,0.001626376,0.005021933,0.001174574,0.0013337,0.0003202983,0.0027545,0.0002398097,0.01356697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6875293,"threshold_uncertainty_score":0.9994944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920207518470299,"score_gpt":0.2778728063360395,"score_spread":0.2586707311513365,"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."}}