{"id":"W2097000000","doi":"10.1109/icde.2005.110","title":"Predicate Derivation and Monotonicity Detection in DB2 UDB","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Predicate (mathematical logic); Rewriting; Schema (genetic algorithms); Search engine indexing; Database; Data mining; Programming language; Information retrieval","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":[0.007903458,0.0007372863,0.001344095,0.002379357,0.0018187,0.004802103,0.003279498,0.001162527,0.002245678],"category_scores_gemma":[0.01777518,0.001549555,0.001321488,0.002747718,0.001897914,0.006179288,0.004973184,0.002390543,0.001850081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002028899,"about_ca_system_score_gemma":0.003076082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008753213,"about_ca_topic_score_gemma":0.006883119,"domain_scores_codex":[0.9860663,0.003641309,0.001514769,0.001331377,0.006673893,0.0007723599],"domain_scores_gemma":[0.990213,0.003472876,0.0005791168,0.003294148,0.002213886,0.0002270574],"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":[0.0007958447,0.0005085477,0.0116797,0.000765568,0.0001424767,0.001477432,0.002160675,0.0265744,0.05073095,0.3333834,0.03494434,0.5368367],"study_design_scores_gemma":[0.0001632135,0.0001250421,0.002108002,0.0001351674,0.0001218008,0.001256513,0.000464769,0.5392801,0.1749323,0.1466065,0.1345969,0.0002097619],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03080426,0.0008672544,0.9352693,0.0009188503,0.0001165441,0.000363307,0.001189437,0.02159428,0.00887674],"genre_scores_gemma":[0.2410908,0.0007070138,0.74077,0.001161391,0.0001321233,0.0005094382,0.005295377,0.004163983,0.006169825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008753213,"threshold_uncertainty_score":0.041798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00816891070638493,"score_gpt":0.2266155199875499,"score_spread":0.218446609281165,"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."}}