{"id":"W2250907725","doi":"","title":"Improved Reordering for Phrase-Based Translation using Sparse Features","year":2013,"lang":"en","type":"article","venue":"NPARC","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Machine translation; Phrase; Artificial intelligence; Translation (biology); Natural language processing; Principle of maximum entropy; Entropy (arrow of time); Pattern recognition (psychology); Speech recognition","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001347303,0.0001081788,0.0001019228,0.00008314516,0.0001068927,0.0002088799,0.0004018389,0.00007175731,0.00001667335],"category_scores_gemma":[0.00004606751,0.00009553518,0.00005230897,0.0001747791,0.00002041069,0.000535673,0.00003285346,0.00009943029,0.000002045826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000331858,"about_ca_system_score_gemma":0.00005017405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004241719,"about_ca_topic_score_gemma":0.000005608445,"domain_scores_codex":[0.9992688,0.00001953527,0.0001274438,0.0002512125,0.000114367,0.000218691],"domain_scores_gemma":[0.9994692,0.00004527061,0.00006652298,0.000275753,0.00009749911,0.00004580463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005488875,0.00001278221,0.00000553717,0.00003845074,0.000003073587,7.447404e-7,0.0001272621,0.00001909375,0.7998903,0.00197192,0.0002688073,0.1976565],"study_design_scores_gemma":[0.0002747999,0.00003985821,0.00002008959,0.0000480525,0.000005254472,0.000003849853,0.000004880185,0.5940886,0.3495349,0.05562231,0.0001922426,0.0001652682],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008278333,0.0003984917,0.9890013,0.001086641,0.00009711116,0.0004390571,0.000001349062,0.0005163106,0.0001814048],"genre_scores_gemma":[0.4221922,5.651779e-7,0.577521,0.0001997556,0.0000337262,0.00002365929,0.000001659509,0.000007802376,0.00001968561],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5940694,"threshold_uncertainty_score":0.3895811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02613576818046439,"score_gpt":0.2777551498492131,"score_spread":0.2516193816687487,"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."}}