{"id":"W2463883732","doi":"10.3906/elk-1410-124","title":"A new dictionary-based preprocessor that uses radix-190 numbering","year":2016,"lang":"en","type":"article","venue":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Preprocessor; Byte; Numbering; Decoding methods; Word (group theory); Natural language processing; Information retrieval; Artificial intelligence; Programming language; Algorithm; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004174292,0.001001925,0.0006890837,0.001712164,0.0005643282,0.001260573,0.0009230329,0.0006818995,0.0131191],"category_scores_gemma":[0.002260335,0.000456354,0.0006395216,0.002046005,0.000415803,0.001418121,0.000857189,0.0009903031,0.007969478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003633929,"about_ca_system_score_gemma":0.001018015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0015225,"about_ca_topic_score_gemma":0.002204894,"domain_scores_codex":[0.9995695,0.00002882369,0.00006108065,0.0001360064,0.0001638632,0.0000406985],"domain_scores_gemma":[0.9990036,0.0002554029,0.00009483275,0.0002598567,0.000340724,0.0000456442],"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":[0.0008847364,0.00009222268,0.001177572,0.0005016741,0.00005287294,0.0003540095,0.0002177647,0.002238019,0.2277422,0.003417012,0.009934266,0.7533877],"study_design_scores_gemma":[0.0001747464,0.001611658,0.006469567,0.0001184139,0.0002014571,0.002514208,0.0003312319,0.06650362,0.7369935,0.002432186,0.1824857,0.000163637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07756756,0.002106031,0.8841311,0.0003019312,0.0007342342,0.0005134142,0.002468728,0.02292383,0.009253057],"genre_scores_gemma":[0.07924202,0.000812934,0.8948009,0.0003473571,0.0002022634,0.0003009052,0.006104528,0.001669979,0.0165191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0131191,"threshold_uncertainty_score":0.04388779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541340196911527,"score_gpt":0.2278800625765778,"score_spread":0.2124666606074625,"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."}}