{"id":"W2997651435","doi":"","title":"ENKRIPSI PESAN TEKS DENGAN ALGORITMA ONE TIME PAD XOR DAN STEGANOGRAFI PADA CITRA GAMBAR DENGAN LEAST SIGNIFICANT BIT","year":2018,"lang":"id","type":"article","venue":"","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Art; Humanities","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":[0.0004421557,0.001125273,0.0007051774,0.0004805427,0.0005651796,0.001502341,0.0006585672,0.0007018847,0.0154084],"category_scores_gemma":[0.001072509,0.0002256527,0.000533567,0.0005254584,0.0004301602,0.00141282,0.0006771929,0.0008608444,0.003445051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005616581,"about_ca_system_score_gemma":0.0007165959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002223104,"about_ca_topic_score_gemma":0.003135861,"domain_scores_codex":[0.9995373,0.00005751486,0.00003919271,0.0001215868,0.00015976,0.00008458371],"domain_scores_gemma":[0.999647,0.00009803754,0.00004357307,0.00005970108,0.0001307602,0.00002089794],"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":[0.00159824,0.0001640214,0.002578111,0.0007793821,0.0001454449,0.000754485,0.0002710161,0.01183737,0.2203178,0.0106732,0.01391592,0.736965],"study_design_scores_gemma":[0.0002126387,0.00197808,0.008103487,0.0003026531,0.0004371713,0.003694951,0.0007900998,0.3113654,0.5120309,0.01344587,0.1474263,0.0002123831],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1682264,0.007208911,0.7727255,0.001692037,0.001553728,0.0004841062,0.001682833,0.01009405,0.03633238],"genre_scores_gemma":[0.6828824,0.003713535,0.23197,0.0008220637,0.0003148429,0.000369554,0.001539579,0.0004197907,0.07796825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0154084,"threshold_uncertainty_score":0.05154622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981848819356362,"score_gpt":0.2160060373501644,"score_spread":0.1961875491566007,"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."}}