{"id":"W4386469341","doi":"10.1007/978-3-031-42935-4","title":"Flexible Query Answering Systems","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Office of Naval Research; Universidad de Alcalá; University of North Carolina at Charlotte; Danmarks Tekniske Universitet; Universidad de Zaragoza; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Otto von Guericke University Magdeburg; Università della Calabria; Universidad de Jaén; Università degli Studi di Milano; Sorbonne Université; Universidad de Granada; University of Bristol; Orta Doğu Teknik Üniversitesi; Universiteit Gent; Università degli Studi di Milano-Bicocca; University College London; Imperial College London; European Commission; University of Alberta; Univerzita Karlova v Praze; Centre National de la Recherche Scientifique; Universidad de Castilla-La Mancha; Louisiana State University","keywords":"Computer science; Question answering; Information retrieval; Query language; Query expansion; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002897667,0.0009586972,0.001505436,0.001682786,0.001630526,0.004268583,0.00373761,0.001679592,0.01888631],"category_scores_gemma":[0.006581888,0.001117928,0.001297247,0.003229186,0.001464439,0.007452343,0.004581976,0.002078041,0.008841465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107857,"about_ca_system_score_gemma":0.0009577953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002583002,"about_ca_topic_score_gemma":0.002921693,"domain_scores_codex":[0.996756,0.0005893557,0.0002862929,0.0007308598,0.001272575,0.0003648949],"domain_scores_gemma":[0.9960813,0.001124447,0.0000982029,0.002135897,0.0004426902,0.0001174665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007779341,0.0002575958,0.00101891,0.0004786392,0.000138801,0.000380939,0.0006024575,0.02268315,0.02532985,0.2294652,0.0813014,0.6375651],"study_design_scores_gemma":[0.0001529184,0.0001820096,0.0008333124,0.0001176653,0.0001613498,0.0006304459,0.0003139349,0.3330001,0.02745927,0.4670621,0.1699819,0.0001049884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01662801,0.001799204,0.9210669,0.001241091,0.00033487,0.000316723,0.002001001,0.02238436,0.03422786],"genre_scores_gemma":[0.2961148,0.001431499,0.6391367,0.0007734309,0.0003733448,0.0004200169,0.01244126,0.002550301,0.04675869],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01888631,"threshold_uncertainty_score":0.06318098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693667206491216,"score_gpt":0.2633665387065202,"score_spread":0.236429866641608,"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."}}