{"id":"W4291713137","doi":"10.1145/1807167.1807201","title":"GRN model of probabilistic databases","year":2010,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Probabilistic logic; Computer science; Probabilistic relevance model; Graphical model; Tuple; Probabilistic database; Formalism (music); Divergence-from-randomness model; Representation (politics); Database; Dependency (UML); Statistical model; Database theory; Theoretical computer science; Data modeling; Data mining; Artificial intelligence; Probabilistic analysis of algorithms; Relational database; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001355933,0.00005727123,0.00007621099,0.00002939862,0.00002529938,0.00002328155,0.0004982368,0.00002162974,0.00002145996],"category_scores_gemma":[0.00005529797,0.00004515116,0.00002174734,0.00009382018,0.0000439457,0.0002260312,0.0001410466,0.0001040193,0.00001891527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001989634,"about_ca_system_score_gemma":0.00008385051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004251417,"about_ca_topic_score_gemma":0.00003819785,"domain_scores_codex":[0.9994528,0.000007451958,0.000125485,0.0001817371,0.0001190653,0.0001134744],"domain_scores_gemma":[0.9992753,0.00003579238,0.00003076247,0.0005305713,0.00007548089,0.00005206839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.09295e-7,0.00003502985,0.00005219364,0.000008049652,0.000001385537,3.056252e-7,0.00004845097,0.001924153,0.01946436,0.9721228,0.0002661003,0.006076588],"study_design_scores_gemma":[0.00004041869,0.00001065973,0.00004092679,0.000004038532,0.000001466003,0.000002227448,0.00000135471,0.9312486,0.005065614,0.06348003,0.00004342231,0.00006125716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03465392,0.000004193589,0.9581816,0.0001813737,0.00009741972,0.00003849171,0.000003279586,0.00009127134,0.006748448],"genre_scores_gemma":[0.6657088,9.349906e-7,0.3339467,0.00007407622,0.000008491119,0.000002498219,7.477383e-7,0.00000179204,0.0002559783],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9293244,"threshold_uncertainty_score":0.1841211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05829657324164689,"score_gpt":0.2806134611353955,"score_spread":0.2223168878937486,"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."}}