{"id":"W2121195856","doi":"10.1145/1925805.1925812","title":"Exploiting uniqueness in query optimization","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Query optimization; Computer science; Exploit; SQL; sort; Sargable; Query by Example; Query language; Conjunctive query; Query expansion; Table (database); Relational database; Uniqueness; Theoretical computer science; Data mining; Web search query; Information retrieval; Database; Mathematics; Search engine","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":[0.00878676,0.0009731988,0.001548236,0.001523254,0.001991872,0.003192091,0.002212881,0.001436525,0.002965035],"category_scores_gemma":[0.0310347,0.0009970223,0.001865343,0.00237383,0.004391709,0.01087935,0.007371011,0.002244995,0.000785169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037179,"about_ca_system_score_gemma":0.00252184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002592298,"about_ca_topic_score_gemma":0.002049898,"domain_scores_codex":[0.9895568,0.003933209,0.0008134443,0.001449542,0.002825095,0.001421827],"domain_scores_gemma":[0.9793444,0.01492221,0.0009598127,0.003041582,0.001491863,0.0002400413],"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":[0.00141721,0.0003717308,0.01899984,0.0009320172,0.000375976,0.001954522,0.001640953,0.1398392,0.03966116,0.47659,0.009105991,0.3091114],"study_design_scores_gemma":[0.0001459816,0.0004618082,0.001844556,0.0001393217,0.0002591826,0.001328543,0.0007290996,0.4758396,0.07053713,0.434056,0.0144846,0.000174195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0625788,0.0007043988,0.9274353,0.001006745,0.00006058821,0.0002072849,0.000189652,0.001669375,0.006147787],"genre_scores_gemma":[0.5735722,0.0004941078,0.422247,0.0006362469,0.0001079361,0.0001836215,0.0003242765,0.0005227025,0.001911937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00878676,"threshold_uncertainty_score":0.04646933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007625288036715054,"score_gpt":0.2320384156873776,"score_spread":0.2244131276506625,"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."}}