{"id":"W7096779754","doi":"","title":"METIS-II: Machine Translation for Low Resource Languages","year":2008,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine translation; Translation (biology); Machine translation software usability; Example-based machine translation; Universal Networking Language; Computer-assisted translation; Transfer-based machine translation; Resource (disambiguation)","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":[0.001139056,0.001159916,0.001225252,0.001259683,0.0008396183,0.002259924,0.001738607,0.0008963469,0.01532251],"category_scores_gemma":[0.00238782,0.0006331927,0.0007233304,0.0009602522,0.0006535583,0.002749787,0.001640064,0.001693682,0.01014407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005950916,"about_ca_system_score_gemma":0.0009408628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006812211,"about_ca_topic_score_gemma":0.001033708,"domain_scores_codex":[0.9989241,0.0002997831,0.00007538634,0.0002575024,0.0003475638,0.00009563557],"domain_scores_gemma":[0.9990771,0.0003140033,0.00006586463,0.0002913148,0.0002006888,0.0000510572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001435284,0.0002612536,0.001170731,0.001973525,0.0002904431,0.0009767924,0.0008944964,0.01101414,0.1525934,0.09421739,0.0800177,0.6551549],"study_design_scores_gemma":[0.000625287,0.0008850088,0.002060471,0.0003485498,0.00024276,0.002397049,0.0005546375,0.2753036,0.261201,0.07764042,0.3785358,0.0002054129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01183849,0.0007092842,0.9186169,0.0004365583,0.0003794474,0.0005178985,0.002451996,0.05233428,0.01271524],"genre_scores_gemma":[0.08132929,0.0004638085,0.8861251,0.0002965274,0.0001824369,0.0006162064,0.009101297,0.006182879,0.01570255],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01532251,"threshold_uncertainty_score":0.05125886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01842030908517424,"score_gpt":0.2790106823640569,"score_spread":0.2605903732788827,"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."}}