{"id":"W2150774720","doi":"10.1145/1142351.1142369","title":"On redundancy vs dependency preservation in normalization","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Redundancy (engineering); Computer science; Functional dependency; Dependency (UML); Normalization (sociology); Theoretical computer science; Data integrity; Data mining; Relational database; Artificial intelligence; Database","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":[0.01260012,0.001073157,0.001285699,0.004002785,0.001795108,0.00349773,0.00247764,0.001903508,0.003471278],"category_scores_gemma":[0.05184603,0.0007768146,0.001782512,0.005279273,0.01010476,0.01795291,0.003883739,0.003325497,0.0006433792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003885357,"about_ca_system_score_gemma":0.001304586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119936,"about_ca_topic_score_gemma":0.0005829919,"domain_scores_codex":[0.987447,0.004173844,0.001044979,0.001549778,0.004903923,0.0008805987],"domain_scores_gemma":[0.9427324,0.03836435,0.003610949,0.01020664,0.004544058,0.0005415677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001480289,0.00006032579,0.001000522,0.0001537727,0.00003357347,0.0002105886,0.0005462907,0.01753662,0.003024336,0.9376488,0.001016884,0.03862018],"study_design_scores_gemma":[0.00002820379,0.0001362941,0.0006058626,0.0000904906,0.00004772482,0.0006875472,0.0001208182,0.04896675,0.008713795,0.9343053,0.006242039,0.00005513199],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1059734,0.00234231,0.860271,0.004178611,0.0001618234,0.0001148987,0.0002701793,0.0003974477,0.02629027],"genre_scores_gemma":[0.7923587,0.00231357,0.1977628,0.001013831,0.0007922925,0.0003298039,0.00030099,0.0003772935,0.004750732],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01260012,"threshold_uncertainty_score":0.06663662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006379026253693026,"score_gpt":0.2189514351828395,"score_spread":0.2125724089291465,"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."}}