{"id":"W2166281503","doi":"","title":"DalTREC 2004: Question Answering using Regular Expression Rewriting","year":2004,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Rewriting; Regular expression; Computer science; Expression (computer science); Question answering; Search engine; Information retrieval; Track (disk drive); Programming language; Natural language processing; World Wide Web; Artificial intelligence; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005057315,0.001410804,0.001673488,0.001758084,0.0009932478,0.003024858,0.003565608,0.002287433,0.01858698],"category_scores_gemma":[0.01051046,0.000895262,0.001245938,0.001162159,0.001083848,0.004356581,0.002328982,0.003061239,0.01112674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00208018,"about_ca_system_score_gemma":0.00190752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0125215,"about_ca_topic_score_gemma":0.01173183,"domain_scores_codex":[0.9944887,0.002135918,0.0003399394,0.001352857,0.001348785,0.0003337977],"domain_scores_gemma":[0.9940136,0.002186389,0.0002003637,0.001783615,0.001572591,0.0002434963],"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":[0.001484157,0.0009335515,0.001584075,0.001932573,0.0003814906,0.0007738547,0.001271727,0.0179405,0.08060946,0.02193745,0.3731783,0.4979728],"study_design_scores_gemma":[0.001070493,0.0007966018,0.003957591,0.0001442709,0.0002500442,0.001388685,0.0005377437,0.2815157,0.1685955,0.02655242,0.5148561,0.0003349071],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05558458,0.003463844,0.5704606,0.003089212,0.0009544568,0.002345422,0.01587123,0.3080067,0.04022398],"genre_scores_gemma":[0.2739885,0.001241686,0.5707157,0.002241914,0.0004075281,0.001047162,0.08058278,0.01279177,0.05698301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01858698,"threshold_uncertainty_score":0.06217957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02825001249352575,"score_gpt":0.2986974757111274,"score_spread":0.2704474632176017,"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."}}