{"id":"W7039609631","doi":"","title":"MODIFIKASI ALGORITMA J-BIT ENCODING UNTUK MENINGKATKAN RASIO KOMPRESI","year":2017,"lang":"id","type":"dissertation","venue":"UAJY Repository (University of Southampton)","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Byte; Encoding (memory); Key (lock); Pattern recognition (psychology)","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","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003092416,0.0007301898,0.0009672822,0.0001871721,0.001666562,0.00009203593,0.001480858,0.001861442,0.000178307],"category_scores_gemma":[0.00007709455,0.0009278905,0.0007862058,0.00009180803,0.0007015685,0.00005117321,0.0003205169,0.0006954864,0.00008808524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009657634,"about_ca_system_score_gemma":0.0005553271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001131538,"about_ca_topic_score_gemma":0.0002797496,"domain_scores_codex":[0.9968954,0.0002711915,0.0005006808,0.001350214,0.0003267086,0.000655816],"domain_scores_gemma":[0.996195,0.00006475039,0.001567768,0.001429021,0.0004348351,0.0003086189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01080349,0.001687096,0.09877548,0.002771675,0.009278649,0.001823746,0.03399931,0.0001993562,0.7389043,0.0003604168,0.005201867,0.09619464],"study_design_scores_gemma":[0.008239112,0.002882372,0.01703751,0.002516048,0.003333161,0.0003525681,0.05687387,0.0005699955,0.3596858,0.0001291773,0.5426429,0.005737496],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6634361,0.002035581,0.0006196623,0.00008621642,0.002364198,0.0006647119,0.0001517535,0.00005074226,0.330591],"genre_scores_gemma":[0.9227204,0.0004365275,0.0007278334,0.0000241845,0.0005756432,0.000003056465,0.00177496,0.00004844658,0.073689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.537441,"threshold_uncertainty_score":0.9996331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126177525203629,"score_gpt":0.2147649837608668,"score_spread":0.2021472312405039,"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."}}