{"id":"W4388496996","doi":"10.18280/ria.370503","title":"Lexical Based Reordering Models for English to Telugu Machine Translation","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"State of New Jersey Department of Education","keywords":"Telugu; Natural language processing; Computer science; Machine translation; Translation (biology); Artificial intelligence; Linguistics; Biology; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004827336,0.0001508116,0.0001664748,0.0002514497,0.000167269,0.0001590035,0.0008139556,0.0000852669,0.00001277402],"category_scores_gemma":[0.0002547021,0.0001493626,0.00009625852,0.001197813,0.00002442713,0.0004145985,0.0001069738,0.0001450065,0.0000645296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003822014,"about_ca_system_score_gemma":0.00003431031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000148276,"about_ca_topic_score_gemma":0.00000964703,"domain_scores_codex":[0.998592,0.00003029537,0.0003220794,0.0005000984,0.000183731,0.0003718399],"domain_scores_gemma":[0.9988698,0.0002778784,0.0000538147,0.0005136747,0.0001796591,0.0001051168],"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":[0.00002863289,0.00006955893,0.0000110241,0.0001609597,0.000007239472,0.00001304782,0.00498501,0.2808541,0.01036198,0.06489722,0.0012105,0.6374007],"study_design_scores_gemma":[0.00002560947,0.00007193541,0.000001014703,0.00006569249,0.000002674041,0.000001401072,0.00004202627,0.8376307,0.1232477,0.03448038,0.004262714,0.0001681432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005828816,0.0004261359,0.9938548,0.002491213,0.000262271,0.0004700063,0.000007857373,0.001466557,0.0004383094],"genre_scores_gemma":[0.5570507,0.000008344022,0.4421354,0.0003332915,0.00007814435,0.0001035832,0.00001287121,0.0000180193,0.0002596336],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6372325,"threshold_uncertainty_score":0.6090829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06599171833415778,"score_gpt":0.313901693747489,"score_spread":0.2479099754133312,"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."}}