{"id":"W15939968","doi":"10.1007/978-1-4419-9380-9_4","title":"Top-k Typicality Queries on Uncertain Data","year":2011,"lang":"en","type":"book-chapter","venue":"˜The œKluwer international series on advances in database systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Object (grammar); Uncertain data; Ranking (information retrieval); Computer science; Set (abstract data type); Variable (mathematics); Section (typography); Artificial intelligence; Mathematics","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.000802453,0.0005433513,0.0005124762,0.0002165488,0.0001682505,0.0003122278,0.006242558,0.0001954677,0.0002289767],"category_scores_gemma":[0.00008972438,0.0003776708,0.00009617406,0.00009532377,0.0003128946,0.00184216,0.001984586,0.000699625,0.0004552607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002228123,"about_ca_system_score_gemma":0.0001095883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002943031,"about_ca_topic_score_gemma":0.0008967189,"domain_scores_codex":[0.9963624,0.000125842,0.0008045718,0.001295819,0.001042073,0.0003692976],"domain_scores_gemma":[0.9950934,0.0003244048,0.0005190552,0.003807423,0.0001537839,0.0001019464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000174989,0.00006487934,0.0000323993,0.0000580011,0.00005881073,0.0001177541,0.00009534771,0.0002319065,8.079215e-7,0.9794318,0.007766268,0.01196703],"study_design_scores_gemma":[0.0002116616,0.0001470578,0.00002884357,0.0005368427,0.000008070278,0.00004597712,0.00004371806,0.001661819,0.000004099557,0.03192274,0.9649464,0.0004427568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00000813477,0.004179034,0.02265505,0.001392401,0.01162117,0.0008408094,0.004847397,0.0002048061,0.9542512],"genre_scores_gemma":[0.1024068,0.03772483,0.02466214,0.01039492,0.01018998,0.0009208365,0.02183346,0.0005543367,0.7913128],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9571801,"threshold_uncertainty_score":0.9998675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0648209263366551,"score_gpt":0.3033923118651761,"score_spread":0.238571385528521,"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."}}