{"id":"W2001023236","doi":"10.1145/1236181.1236184","title":"Statistical query translation models for cross-language information retrieval","year":2006,"lang":"en","type":"article","venue":"ACM Transactions on Asian Language Information Processing","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Cross-language information retrieval; Natural language processing; Query expansion; Artificial intelligence; Machine translation; Query language; RDF query language; Translation (biology); Dependency (UML); Query optimization; Context (archaeology); Information retrieval; Web query classification; Web search query; Search engine","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":[0.01093543,0.001927331,0.002091525,0.003335338,0.001000239,0.002254909,0.002622167,0.001954855,0.004018032],"category_scores_gemma":[0.02368716,0.001017366,0.002663944,0.004964612,0.001510898,0.005766263,0.001705718,0.002308671,0.004110179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002117966,"about_ca_system_score_gemma":0.001930452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004970478,"about_ca_topic_score_gemma":0.00472648,"domain_scores_codex":[0.9893519,0.006758378,0.0006463814,0.001008171,0.001969141,0.0002659435],"domain_scores_gemma":[0.9831176,0.01167289,0.001141915,0.002050868,0.001899307,0.000117411],"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":[0.0006370458,0.0003882385,0.002644269,0.0009888009,0.0006410162,0.0003534484,0.0005833211,0.4043848,0.006629382,0.1435359,0.01563971,0.423574],"study_design_scores_gemma":[0.00004511391,0.0001167858,0.0003540226,0.00002139458,0.0000607746,0.0001454581,0.00004308364,0.936632,0.00121168,0.05648566,0.004835965,0.00004815789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003893093,0.001468259,0.9912966,0.0004483676,0.0001003473,0.0001630738,0.000256553,0.001360623,0.001013031],"genre_scores_gemma":[0.3119328,0.003978833,0.6711147,0.0009181272,0.0008314403,0.002188966,0.003023264,0.0008937448,0.005118066],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01093543,"threshold_uncertainty_score":0.05783278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185437753511291,"score_gpt":0.2911378651152146,"score_spread":0.2792834875801017,"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."}}