{"id":"W4401429991","doi":"10.36040/jati.v8i4.10337","title":"PREDIKSI ADOPSI HEWAN PELIHARAAN MENGGUNAKAN METODE XGBOOST","year":2024,"lang":"id","type":"article","venue":"JATI (Jurnal Mahasiswa Teknik Informatika)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001922448,0.001025701,0.0008798461,0.001066629,0.001117325,0.00502668,0.003357043,0.0004353948,0.0003796955],"category_scores_gemma":[0.0004355582,0.0009627921,0.0005555891,0.002430252,0.0003046606,0.005129004,0.001382424,0.002339391,0.008754387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003388937,"about_ca_system_score_gemma":0.001442683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001819706,"about_ca_topic_score_gemma":0.00004304997,"domain_scores_codex":[0.9934012,0.0003125019,0.002015596,0.001151144,0.001608602,0.00151101],"domain_scores_gemma":[0.9952121,0.0006115877,0.0006917825,0.0022439,0.0003723774,0.000868258],"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":[0.00006713768,0.0003988112,0.0003777467,0.001965617,0.0009186132,0.0001799534,0.02675215,0.0006311678,0.0005010812,0.06172258,0.4301937,0.4762915],"study_design_scores_gemma":[0.0007075472,0.0003272656,0.002114425,0.001109162,0.0002247305,0.000467532,0.0007542417,0.1174111,0.0006242898,0.000813884,0.8742709,0.001174941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02483405,0.01068505,0.3820942,0.04118218,0.01119069,0.00348703,0.002057554,0.006852947,0.5176163],"genre_scores_gemma":[0.8703629,0.00094052,0.05353404,0.003445741,0.002804061,0.0004831645,0.0009953172,0.0002744991,0.06715976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8455288,"threshold_uncertainty_score":0.9999623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01417810789291214,"score_gpt":0.2719171737827221,"score_spread":0.2577390658898099,"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."}}