{"id":"W3188280450","doi":"10.48550/arxiv.2108.03533","title":"Improving Similar Language Translation With Transfer Learning","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Catalan; Machine translation; Portuguese; Computer science; Natural language processing; Task (project management); Artificial intelligence; Transfer of learning; Rank (graph theory); Translation (biology); Linguistics; Mathematics; Philosophy; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003098338,0.001976436,0.001432744,0.001497984,0.0009415321,0.00202502,0.002403444,0.001849403,0.01001829],"category_scores_gemma":[0.01137461,0.0004524911,0.001450884,0.001950545,0.0009616741,0.004888455,0.002851504,0.002870192,0.009273098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092772,"about_ca_system_score_gemma":0.001528836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004701952,"about_ca_topic_score_gemma":0.004809899,"domain_scores_codex":[0.9977894,0.0008446,0.0001128016,0.0006843687,0.0003621307,0.0002066925],"domain_scores_gemma":[0.9960646,0.001540928,0.000173099,0.001378919,0.0007150704,0.0001273595],"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":[0.0005557011,0.00111285,0.002845753,0.0005217461,0.0003884811,0.0003648826,0.0003513063,0.2444644,0.01470328,0.01535852,0.03202725,0.6873059],"study_design_scores_gemma":[0.0001042903,0.0003078459,0.0004924033,0.00004402072,0.00008342598,0.0001531595,0.0001058973,0.9457192,0.01241176,0.03263713,0.007902328,0.00003845199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1149062,0.003923305,0.8230768,0.002031552,0.001315659,0.0004189658,0.00131758,0.02674222,0.0262678],"genre_scores_gemma":[0.6981493,0.00141469,0.2658813,0.001442427,0.0007001123,0.0004295673,0.007322278,0.002287933,0.02237241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01001829,"threshold_uncertainty_score":0.0335145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246287500554876,"score_gpt":0.1845435082292529,"score_spread":0.1520806332237041,"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."}}