{"id":"W4387216869","doi":"10.59697/jik.v2i1.433","title":"ANALISA ALGORITMA ELGAMAL DALAM PENYANDIAN DATA SEBAGAI KEAMANAN DATABASE","year":2018,"lang":"id","type":"article","venue":"Jurnal Informatika Kaputama (JIK)","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Database; Operating system","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":[0.003954228,0.0007225078,0.0007480447,0.003025323,0.001518054,0.006978299,0.001253114,0.0009099307,0.01710988],"category_scores_gemma":[0.0165713,0.0004175392,0.0007026584,0.005841868,0.0007698999,0.00646334,0.001454316,0.001310176,0.008184894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002082834,"about_ca_system_score_gemma":0.002371654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008075383,"about_ca_topic_score_gemma":0.005720787,"domain_scores_codex":[0.9908196,0.001326571,0.0008724872,0.001071292,0.005299043,0.0006109949],"domain_scores_gemma":[0.9849247,0.004962376,0.0006893872,0.003276377,0.005912262,0.0002347161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001211714,0.0002923922,0.03310685,0.00173799,0.0002468464,0.001167447,0.003809513,0.005493903,0.03047291,0.02169897,0.0523359,0.8484256],"study_design_scores_gemma":[0.0001077573,0.0005524135,0.03414434,0.0005981745,0.000424568,0.003815336,0.011709,0.0594673,0.1177965,0.01645246,0.7547266,0.0002055982],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4410153,0.01727117,0.3104014,0.009312127,0.001928778,0.002315328,0.0184409,0.03085078,0.1684641],"genre_scores_gemma":[0.7312014,0.004820176,0.1705175,0.001284598,0.0002183701,0.0007234272,0.01035749,0.002148166,0.07872902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01710988,"threshold_uncertainty_score":0.05723822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06036008029892474,"score_gpt":0.3114478069273863,"score_spread":0.2510877266284615,"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."}}