{"id":"W1984389168","doi":"10.1109/icdim.2010.5664250","title":"Exploiting Wikipedia in query understanding systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Exploit; Computer science; Encyclopedia; Resource (disambiguation); Information retrieval; Query expansion; Knowledge base; Web query classification; Query optimization; Query language; Web search query; Artificial intelligence; 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":[0.006689808,0.0009290639,0.001138512,0.005202142,0.001459746,0.004400174,0.00224391,0.001330177,0.002204355],"category_scores_gemma":[0.02233527,0.0006964105,0.001043421,0.003948779,0.001169651,0.01363864,0.003848426,0.001388637,0.001045896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276785,"about_ca_system_score_gemma":0.001532428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00617148,"about_ca_topic_score_gemma":0.008294786,"domain_scores_codex":[0.993228,0.002766176,0.0007390174,0.001080282,0.001856918,0.0003295246],"domain_scores_gemma":[0.9833582,0.01118894,0.0007600226,0.00200884,0.002388749,0.0002953338],"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":[0.001350561,0.001051455,0.01406355,0.002175866,0.0004779408,0.001392016,0.005230484,0.04071115,0.05239686,0.07330507,0.03367006,0.7741749],"study_design_scores_gemma":[0.0001762273,0.0003930505,0.003406774,0.0002177905,0.00037319,0.001053559,0.002374731,0.7072039,0.0927044,0.1053106,0.08658102,0.0002047227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06467708,0.001655349,0.9050634,0.002232612,0.000118133,0.0007849663,0.001688585,0.01838117,0.005398695],"genre_scores_gemma":[0.3337364,0.001086358,0.655362,0.0006428015,0.0001181236,0.0004423838,0.00552828,0.0007450657,0.002338664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006689808,"threshold_uncertainty_score":0.03537947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07216335139671823,"score_gpt":0.3582540733684273,"score_spread":0.286090721971709,"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."}}