{"id":"W4290988756","doi":"10.47709/dsi.v2i1.1664","title":"Penggunaan Metode Backpropagation Pada Sistem Prediksi Kelulusan Mahasiswa STMIK Kaputama Binjai","year":2022,"lang":"id","type":"article","venue":"Data Sciences Indonesia (DSI)","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":"Humanities; Physics; 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":[0.001226577,0.001697246,0.001127728,0.001026971,0.0008899376,0.002661788,0.001303121,0.001680811,0.01085895],"category_scores_gemma":[0.003388447,0.0006142673,0.001263462,0.001195764,0.0005677755,0.002764681,0.00114073,0.002592561,0.005353865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117979,"about_ca_system_score_gemma":0.002130935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009662803,"about_ca_topic_score_gemma":0.01124026,"domain_scores_codex":[0.9991905,0.0001097274,0.00007821888,0.000200302,0.0003185818,0.000102526],"domain_scores_gemma":[0.9986326,0.0004066958,0.00009118111,0.0001157194,0.0006894005,0.00006441288],"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":[0.0005251846,0.0002513972,0.005564455,0.000939378,0.0003275838,0.0006159769,0.0003671471,0.09620903,0.04043373,0.009657648,0.02792001,0.8171884],"study_design_scores_gemma":[0.00009490043,0.0003564043,0.007860349,0.00033834,0.00029204,0.0008434966,0.0004047871,0.8430275,0.05628949,0.01805611,0.0722594,0.0001770648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05391148,0.00521797,0.8954321,0.003554944,0.001430885,0.0003069952,0.001462599,0.007783996,0.0308991],"genre_scores_gemma":[0.4925577,0.00794585,0.4105194,0.001288619,0.0006507465,0.0005879066,0.003284173,0.001429618,0.08173595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01085895,"threshold_uncertainty_score":0.03632683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06527736712589116,"score_gpt":0.3158957903005611,"score_spread":0.25061842317467,"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."}}