{"id":"W893501441","doi":"","title":"Data Mining: Implementasi Regresi Linear Untuk Prediksi Nilai Ujian","year":2013,"lang":"id","type":"article","venue":"","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Linear regression; Statistics; Data mining; Proper linear model; Computer science; Linear model; Mathematics; Bayesian multivariate linear regression","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":[0.00422561,0.001134588,0.000817424,0.001861158,0.000574876,0.002068937,0.001699215,0.0004675453,0.009380144],"category_scores_gemma":[0.009604743,0.0006453909,0.001228514,0.001918751,0.0004763027,0.001609333,0.001580333,0.00146388,0.007642727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004469001,"about_ca_system_score_gemma":0.001038746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00170214,"about_ca_topic_score_gemma":0.001454041,"domain_scores_codex":[0.9981315,0.000523763,0.0002884632,0.0004242068,0.000527108,0.000105021],"domain_scores_gemma":[0.9974136,0.001346638,0.0001860224,0.0004771191,0.0005227468,0.00005396495],"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":[0.001162755,0.0003681456,0.007548108,0.001458879,0.0004890588,0.0005396003,0.0009311238,0.02217108,0.009780468,0.0217707,0.03556806,0.898212],"study_design_scores_gemma":[0.0004859453,0.0005609864,0.006990097,0.0004692736,0.0003788065,0.001645151,0.0006070741,0.6261209,0.09137615,0.06034316,0.2108187,0.0002037438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01136864,0.0005207583,0.9102023,0.0003947243,0.00009920891,0.000364889,0.002572713,0.0700005,0.0044762],"genre_scores_gemma":[0.07970683,0.0004276697,0.909031,0.0001701376,0.00004611817,0.0009154268,0.004220131,0.001897326,0.003585296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009380144,"threshold_uncertainty_score":0.03137964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06588370321750264,"score_gpt":0.3365054392107181,"score_spread":0.2706217359932154,"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."}}