{"id":"W2110939313","doi":"10.1002/asi.10214","title":"Query expansion and query translation as logical inference","year":2003,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Query expansion; Web query classification; Computer science; Sargable; RDF query language; Query optimization; Inference; Query language; Web search query; Information retrieval; Set (abstract data type); Translation (biology); Boolean conjunctive query; Natural language processing; Artificial intelligence; Search engine; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001192139,0.00007130414,0.0001373396,0.000211371,0.0002985497,0.0001608118,0.0006005364,0.00005608939,3.344078e-7],"category_scores_gemma":[0.0006746381,0.00004351946,0.00006179424,0.001628821,0.001077451,0.002789543,0.0001060995,0.0002044263,3.539905e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004610003,"about_ca_system_score_gemma":0.0002935094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004726568,"about_ca_topic_score_gemma":3.522019e-7,"domain_scores_codex":[0.9991276,0.00001497771,0.0002691311,0.00009156022,0.0003426116,0.0001541735],"domain_scores_gemma":[0.9986051,0.00009608977,0.0005384008,0.0001630064,0.0005543687,0.00004298781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009906726,0.00001644275,0.0007350051,0.00002192989,0.00001065488,4.074602e-7,0.001557246,0.000006400584,0.01665382,0.3095724,0.0003666532,0.6710492],"study_design_scores_gemma":[0.001795705,0.002494266,0.002971252,0.0002692906,0.0000667697,0.002447698,0.01150331,0.02468895,0.2100976,0.6767927,0.06600191,0.0008705467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3943084,0.0005435283,0.5961881,0.008436051,0.0001172916,0.0001791007,9.121442e-7,0.0000951055,0.0001316116],"genre_scores_gemma":[0.7528237,0.0001365308,0.2459165,0.001111454,0.000005319063,0.000003104936,6.252752e-8,0.000001105684,0.00000222325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6701787,"threshold_uncertainty_score":0.3969914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541196678103727,"score_gpt":0.2992683814853831,"score_spread":0.2838564147043458,"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."}}