{"id":"W1557439938","doi":"","title":"Shallow-Transfer Rule-Based Machine Translation between Icelandic and Swedish. Developing Apertium-is-sv: A Bidirectional Open-Source RBMT Application for Icelandic and Swedish","year":2013,"lang":"en","type":"article","venue":"Skemman","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta-Pacific Forest Industries","keywords":"Icelandic; Translation (biology); Computer science; Open source; Artificial intelligence; Chemistry; Linguistics; Software","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001062803,0.0007698312,0.0004868507,0.0008691952,0.0006989411,0.001563634,0.0007568896,0.000655068,0.009035722],"category_scores_gemma":[0.002683695,0.0003936643,0.0004974093,0.0005930326,0.0005263361,0.001482199,0.001240036,0.0007016072,0.006341724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006539412,"about_ca_system_score_gemma":0.001908885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004674482,"about_ca_topic_score_gemma":0.008340916,"domain_scores_codex":[0.9992448,0.0002286511,0.0001081254,0.0002097564,0.0001569968,0.00005159983],"domain_scores_gemma":[0.9989263,0.0005187501,0.00008179429,0.00014936,0.0002878297,0.00003584903],"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":[0.0004166252,0.0002092499,0.003727728,0.001346031,0.0001232782,0.00126764,0.002769885,0.01845573,0.1019961,0.03024236,0.05275665,0.7866887],"study_design_scores_gemma":[0.0001718554,0.0002916704,0.005982596,0.0004921775,0.0001748475,0.002090208,0.002211133,0.196558,0.3065538,0.03417462,0.4511261,0.0001729338],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.1117395,0.001040664,0.7387512,0.0009622811,0.0006246908,0.0005323442,0.00920008,0.06065452,0.07649484],"genre_scores_gemma":[0.3022248,0.0005669963,0.6434869,0.0003652106,0.00009211898,0.0003098555,0.01955728,0.004604443,0.02879236],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.009035722,"threshold_uncertainty_score":0.03022754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240229384020454,"score_gpt":0.2746513759470874,"score_spread":0.2522490821068828,"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."}}