{"id":"W143535644","doi":"10.1007/978-3-540-69052-8_39","title":"Efficient Handling of Relational Database Combinatorial Queries Using CSPs","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Tuple; Constraint (computer-aided design); Relational database; SQL; Database; Constraint satisfaction problem; Combinatorial explosion; Backtracking; Theoretical computer science; Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003389104,0.001491849,0.003200283,0.001627345,0.001858915,0.00637364,0.005559795,0.001446015,0.008930068],"category_scores_gemma":[0.01377024,0.001491832,0.002940892,0.005755391,0.001810639,0.009414021,0.006088942,0.003909331,0.002215331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391485,"about_ca_system_score_gemma":0.002641805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003930856,"about_ca_topic_score_gemma":0.006472237,"domain_scores_codex":[0.9931945,0.00168846,0.0006874255,0.0007620798,0.002880888,0.0007866849],"domain_scores_gemma":[0.9874751,0.007910335,0.0005487555,0.002553483,0.001189305,0.0003230333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001276195,0.0006066797,0.001658621,0.001862062,0.0003115484,0.001283947,0.0009298014,0.1475078,0.02176288,0.3561747,0.04826058,0.4183652],"study_design_scores_gemma":[0.0002206482,0.0001273747,0.0002792275,0.00009134844,0.0001143426,0.0005830557,0.0004385229,0.7051918,0.0152317,0.2588342,0.01880911,0.0000788391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02122419,0.0006016603,0.9617321,0.0006216278,0.0001115454,0.000363182,0.0009906649,0.006237077,0.008117935],"genre_scores_gemma":[0.2185653,0.0007606241,0.7688746,0.0003650935,0.0001716133,0.000378249,0.002834214,0.001981192,0.006069009],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008930068,"threshold_uncertainty_score":0.02987403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02573494655154039,"score_gpt":0.2454284780145643,"score_spread":0.2196935314630239,"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."}}