{"id":"W4384573799","doi":"10.59697/jsik.v6i2.187","title":"PENERAPAN ALGORITMA FIXED LENGTH BINARY ENCODING (FLBE) KOMPRESI CITRA","year":2022,"lang":"id","type":"article","venue":"Jurnal Sistem Informasi Kaputama (JSIK)","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":"Computer science; Physics","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":[0.0004355068,0.0006834301,0.0005126934,0.0007242823,0.0004284779,0.001395357,0.0007529308,0.0007397594,0.009161663],"category_scores_gemma":[0.001558572,0.0002156581,0.0004267608,0.0007996423,0.0002999502,0.00166907,0.0005914724,0.0006978771,0.002929494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005369546,"about_ca_system_score_gemma":0.0007518231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00219042,"about_ca_topic_score_gemma":0.002444985,"domain_scores_codex":[0.9995658,0.00004336438,0.00004621405,0.0000712057,0.0002051282,0.00006829497],"domain_scores_gemma":[0.9993839,0.0001880673,0.00005555633,0.0001010909,0.0002363962,0.00003497884],"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":[0.001139232,0.0001412049,0.001833836,0.0006808098,0.00004989007,0.0005494703,0.0004927915,0.006318604,0.2462371,0.00890719,0.01840347,0.7152465],"study_design_scores_gemma":[0.0001315436,0.0009511141,0.005674221,0.0002620787,0.0001378526,0.002610708,0.0005822312,0.1375678,0.6295844,0.007968757,0.2143464,0.0001829039],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1510812,0.006686814,0.7672893,0.001562116,0.0008654515,0.0004435373,0.002415172,0.02863402,0.04102243],"genre_scores_gemma":[0.4712899,0.003398904,0.4543828,0.0007508821,0.0001491971,0.0003572456,0.003771894,0.001249295,0.06464985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009161663,"threshold_uncertainty_score":0.03064877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710262864551259,"score_gpt":0.2166492956883619,"score_spread":0.1995466670428493,"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."}}