{"id":"W6910396119","doi":"10.4224/21274926","title":"Machine translation: benefits and advantages of statistical machine translation and NRC's Portage","year":2015,"lang":"en","type":"report","venue":"NPARC","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine translation; Service (business); Machine translation software usability; Statistical analysis; Key (lock); Statistical model","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01905027,0.001173933,0.0007755044,0.004274917,0.001316955,0.005588979,0.001933017,0.001776415,0.02019568],"category_scores_gemma":[0.05444294,0.0006698968,0.000872031,0.00828557,0.00211261,0.008091643,0.003468241,0.003527305,0.01454094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001989094,"about_ca_system_score_gemma":0.005128444,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009240801,"about_ca_topic_score_gemma":0.009787383,"domain_scores_codex":[0.9747838,0.008609847,0.001187432,0.001660609,0.01319765,0.0005606727],"domain_scores_gemma":[0.95055,0.02039828,0.002047165,0.01006138,0.01588529,0.001057972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00105142,0.0004072985,0.007792352,0.0005940829,0.000091052,0.0007386609,0.0005304277,0.009422822,0.007648327,0.08789191,0.1683425,0.7154891],"study_design_scores_gemma":[0.000276872,0.0007893685,0.01649923,0.0005709075,0.0001540318,0.005582441,0.0005318982,0.08685599,0.03192025,0.08804961,0.7685263,0.0002431121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07051724,0.01978506,0.3015205,0.07903521,0.004251254,0.001000899,0.0133988,0.03382343,0.4766676],"genre_scores_gemma":[0.4109272,0.01389089,0.4383897,0.004013652,0.005514747,0.0007175163,0.03612735,0.007832806,0.08258601],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9907592,"threshold_uncertainty_score":0.1007487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05761096328401982,"score_gpt":0.3275210822577028,"score_spread":0.269910118973683,"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."}}