{"id":"W4390117639","doi":"10.29137/umagd.1294273","title":"İstatiksel Kodlama Yöntemlerinin Türkçe ve İngilizce Metinlerde Sıkıştırma Başarımı Karşılaştırma Örneği","year":2023,"lang":"tr","type":"article","venue":"Uluslararası mühendislik araştırma ve geliştirme dergisi","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics; Mathematics","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":[0.002106506,0.001241061,0.0007798954,0.001775404,0.004091374,0.008951442,0.001177063,0.002321405,0.04589554],"category_scores_gemma":[0.005055149,0.000597787,0.001001488,0.002187119,0.003281568,0.005207903,0.003523104,0.002734147,0.01554506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003385158,"about_ca_system_score_gemma":0.005704222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01245901,"about_ca_topic_score_gemma":0.01738882,"domain_scores_codex":[0.9972661,0.0005304362,0.0001739669,0.0004422817,0.001155406,0.000431882],"domain_scores_gemma":[0.9962924,0.000654979,0.0005322035,0.0004196443,0.001721196,0.0003796174],"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":[0.0007696014,0.0004868567,0.04307971,0.003371473,0.0002396142,0.003950859,0.02441245,0.00417272,0.01517356,0.2125712,0.1053565,0.5864155],"study_design_scores_gemma":[0.00004087132,0.0002620982,0.03566404,0.001404054,0.0001537789,0.002209508,0.02503548,0.002301466,0.009877943,0.03072892,0.8920983,0.0002235851],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1855581,0.02163467,0.06137215,0.02341498,0.003377197,0.0004984452,0.002673768,0.002209093,0.6992616],"genre_scores_gemma":[0.6867329,0.01551632,0.03432095,0.002495953,0.0005866005,0.00030036,0.002454465,0.0007367848,0.2568556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04589554,"threshold_uncertainty_score":0.1535359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02629490577461008,"score_gpt":0.2755927664724364,"score_spread":0.2492978606978263,"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."}}