{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0115627,0.001588356,0.001751949,0.01016402,0.001576433,0.004476099,0.002356051,0.002418784,0.004396713],"category_scores_gemma":[0.0278323,0.000605192,0.00199888,0.006833223,0.001121753,0.006111993,0.002570639,0.001926867,0.004474521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001655398,"about_ca_system_score_gemma":0.00163819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005982258,"about_ca_topic_score_gemma":0.004957814,"domain_scores_codex":[0.9841875,0.008795626,0.001479378,0.002497297,0.002463596,0.0005766855],"domain_scores_gemma":[0.9657149,0.0221302,0.001765636,0.004105696,0.005731643,0.0005519491],"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":[0.0004096244,0.0008747241,0.007766747,0.0009584005,0.0002484726,0.0002371851,0.002199991,0.009939582,0.0253653,0.0202163,0.02780082,0.9039829],"study_design_scores_gemma":[0.0002265242,0.0005609731,0.01128531,0.0005157277,0.0004871272,0.001176698,0.001598745,0.6890668,0.07258618,0.112673,0.109455,0.0003679264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01325611,0.000803504,0.9700169,0.0006111961,0.0001724821,0.0009009062,0.001182528,0.007510925,0.005545545],"genre_scores_gemma":[0.1223879,0.0005987462,0.8638506,0.0004820834,0.0002803831,0.0007917214,0.006589117,0.0004476947,0.004571813],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0115627,"threshold_uncertainty_score":0.06115013,"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."}}