{"id":"W4417142765","doi":"10.56971/jwi.v9i2.323","title":"ANALISIS KLASIFIKASI SARAN PESERTA PELATIHAN MENGGUNAKAN PENDEKATAN MACHINE LEARNING","year":2024,"lang":"","type":"article","venue":"Jurnal Kewidyaiswaraan/Jurnal kewidyaiswaraan","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":"Naive Bayes classifier; AdaBoost","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","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.005963367,0.003878937,0.003295361,0.003950606,0.0050454,0.01091101,0.008605481,0.001535476,0.002075337],"category_scores_gemma":[0.001506443,0.003879855,0.002630463,0.008731646,0.001151688,0.006672786,0.003205384,0.007969175,0.005320536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001490892,"about_ca_system_score_gemma":0.002980508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002934599,"about_ca_topic_score_gemma":0.0004439066,"domain_scores_codex":[0.9755079,0.002809536,0.005168378,0.006353687,0.004943965,0.005216522],"domain_scores_gemma":[0.9861352,0.002221413,0.002049428,0.004847922,0.001124852,0.003621157],"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":[0.001194618,0.00383474,0.08784956,0.004558822,0.007958642,0.008497029,0.02389177,0.01358829,0.006401529,0.08664068,0.04837634,0.707208],"study_design_scores_gemma":[0.002910092,0.002403307,0.02401618,0.003562597,0.001763918,0.005627943,0.0008552201,0.491065,0.0009706197,0.00186968,0.4596567,0.005298734],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2717606,0.1419755,0.38354,0.04742687,0.02986229,0.00645237,0.003746212,0.01294242,0.1022937],"genre_scores_gemma":[0.9683223,0.005648985,0.005560091,0.001010691,0.003857522,0.0002234959,0.001098105,0.0007650678,0.01351377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7019092,"threshold_uncertainty_score":0.9997607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203131134102322,"score_gpt":0.2843137575026259,"score_spread":0.2640006440923937,"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."}}