{"id":"W4285009242","doi":"10.36341/rabit.v7i2.2489","title":"IMPLEMENTASI ALGORITMA C4.5 UNTUK KLASIFIKASI PRODUK LARIS SEPEDA MOTOR HONDA PADA CV CENDANA MOTOR CEPIRING","year":2022,"lang":"id","type":"article","venue":"Rabit Jurnal Teknologi dan Sistem Informasi Univrab","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Physics; Humanities; 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","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002698709,0.001250343,0.001262847,0.0009510665,0.004247003,0.001257862,0.005871825,0.0003645572,0.0002265055],"category_scores_gemma":[0.0004200223,0.001320356,0.0006919625,0.002464687,0.000410292,0.002086,0.005513326,0.003690514,0.000256927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00161144,"about_ca_system_score_gemma":0.001475548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004659332,"about_ca_topic_score_gemma":0.00007592375,"domain_scores_codex":[0.9905084,0.0008879346,0.002362214,0.001887289,0.00193153,0.002422679],"domain_scores_gemma":[0.9930553,0.0005090447,0.001926786,0.003253707,0.0004406897,0.0008144844],"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":[0.0006982659,0.003145227,0.04915863,0.00177899,0.002289598,0.00139027,0.01672995,0.003072572,0.01369665,0.09127197,0.05005188,0.766716],"study_design_scores_gemma":[0.002274197,0.002174919,0.0112796,0.0001374494,0.000205581,0.001222158,0.00603603,0.01335493,0.00101798,0.0001017876,0.960615,0.001580323],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7569111,0.007963276,0.08761898,0.03084028,0.01672591,0.01212566,0.005787487,0.008050892,0.0739764],"genre_scores_gemma":[0.8835586,0.001093038,0.03099174,0.003038797,0.001268193,0.001214928,0.002274781,0.0003545492,0.07620541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9105632,"threshold_uncertainty_score":0.9997789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035937868703847,"score_gpt":0.2628968829321344,"score_spread":0.242537504245096,"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."}}