{"id":"W3013936196","doi":"","title":"ANALISA DAN PERBANDINGAN METODE ALGORITMA APRIORI DAN FP-GROWTH UNTUK MENCARI POLA DAERAH STRATEGIS PENGENALAN KAMPUS STUDI KASUS DI STKIP ADZKIA PADANG","year":2018,"lang":"id","type":"article","venue":"","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Humanities; Computer science; Mathematics; Philosophy","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":[0.005033273,0.001746381,0.001368067,0.001892301,0.0009971575,0.006464788,0.001330659,0.001346323,0.009299986],"category_scores_gemma":[0.01045861,0.0004979669,0.0015361,0.002724644,0.0005353055,0.00349105,0.00130845,0.001847572,0.004269017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001876298,"about_ca_system_score_gemma":0.002716157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005780877,"about_ca_topic_score_gemma":0.005756419,"domain_scores_codex":[0.9963632,0.0007999816,0.0003113823,0.000660717,0.001512152,0.000352582],"domain_scores_gemma":[0.9918927,0.004377762,0.0006035277,0.0006016003,0.002245183,0.0002792519],"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":[0.002119175,0.0007602666,0.04448954,0.004615212,0.0004925583,0.0009119702,0.002785648,0.03292646,0.04697171,0.01200944,0.02149819,0.8304198],"study_design_scores_gemma":[0.0004023976,0.00442395,0.07447553,0.002493507,0.00213893,0.002049484,0.01699538,0.3128412,0.1709565,0.03764461,0.375024,0.0005544781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4996048,0.02928422,0.3391539,0.009657234,0.001445772,0.001949479,0.008551571,0.005503078,0.1048498],"genre_scores_gemma":[0.7438717,0.0108287,0.2003079,0.001032073,0.0003003721,0.001263888,0.005141255,0.0006502228,0.03660388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009299986,"threshold_uncertainty_score":0.0311116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0259836335049272,"score_gpt":0.2926541658426853,"score_spread":0.2666705323377581,"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."}}