{"id":"W4390776420","doi":"10.1007/978-3-031-45043-3_8","title":"Correction to: Natural Language Interfaces to Databases","year":2024,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Natural (archaeology); Database; Natural language processing; Information retrieval; Programming language; History; Archaeology","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":[0.003906548,0.002094246,0.002322032,0.006553338,0.005255555,0.006190939,0.004742944,0.010225,0.1100134],"category_scores_gemma":[0.06400321,0.00132283,0.001731954,0.004958934,0.003628703,0.005141577,0.003053485,0.01295898,0.07628045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006006018,"about_ca_system_score_gemma":0.005163759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01918308,"about_ca_topic_score_gemma":0.02363202,"domain_scores_codex":[0.9929063,0.001017289,0.0009828525,0.001016751,0.00341969,0.0006571104],"domain_scores_gemma":[0.9522734,0.008647042,0.001560439,0.00477604,0.03140397,0.001339055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001261548,0.000005174354,0.00002274877,0.0000494321,0.000005436553,0.00005747955,0.00002385795,0.00002270501,0.0000315986,0.001833174,0.9937404,0.004195472],"study_design_scores_gemma":[0.00002731559,0.0000120488,0.000397957,0.0001308337,0.00002340155,0.0002339295,0.00007724401,0.0004514771,0.000405624,0.00587312,0.9923372,0.00002986893],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001878641,0.000839583,0.003560304,0.1270631,0.85374,0.00005351068,0.001288356,0.002309675,0.01095745],"genre_scores_gemma":[0.01819048,0.003739087,0.01120059,0.1850164,0.3429898,0.0003949265,0.002780677,0.0041211,0.4315669],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1100134,"threshold_uncertainty_score":0.3680316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388686777096952,"score_gpt":0.2988206662821468,"score_spread":0.2599519885724516,"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."}}