{"id":"W1977123279","doi":"10.1080/08839510903078093","title":"QUESTION ANSWERING USING QUESTION CLASSIFICATION AND DOCUMENT TAGGING","year":2009,"lang":"en","type":"article","venue":"Applied Artificial Intelligence","topic":"Topic Modeling","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Question answering; Computer science; Information retrieval; Document retrieval; Document classification; Natural language processing; Artificial intelligence","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":[0.0005104362,0.0001325401,0.0001144167,0.0001074891,0.0002013649,0.0002702687,0.0002684036,0.00006556461,0.000003249549],"category_scores_gemma":[0.00002704626,0.0001436598,0.00002063374,0.0002373489,0.00003583985,0.000426935,0.00006345053,0.000131107,0.00002061472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009185538,"about_ca_system_score_gemma":0.00002683412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005105459,"about_ca_topic_score_gemma":0.000007043765,"domain_scores_codex":[0.9987094,0.00003697017,0.0003477177,0.000457957,0.0002099374,0.0002379808],"domain_scores_gemma":[0.9993997,0.00003699639,0.0001118334,0.0003282443,0.00004858146,0.00007466025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002807685,0.000008899797,0.00001091348,0.000002681984,0.000001078722,8.266246e-7,0.0002749256,0.004541549,0.04748219,0.5840794,7.935434e-7,0.363594],"study_design_scores_gemma":[0.00001236793,0.00002336806,0.0003475351,0.00003318949,0.000004591353,0.000006746292,0.0001105322,0.6773697,0.0468302,0.2750174,0.00007904332,0.0001653718],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0896405,0.00005314253,0.9082658,0.000951722,0.0001803991,0.0001768541,1.396421e-7,0.0001900927,0.0005413067],"genre_scores_gemma":[0.8618839,0.0000210784,0.1377421,0.0002234183,0.0001104082,0.00000686005,0.000001167777,0.000004883639,0.000006185815],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7722434,"threshold_uncertainty_score":0.5858275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06235094333815122,"score_gpt":0.3230424587390867,"score_spread":0.2606915154009355,"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."}}