{"id":"W2118336583","doi":"10.1007/11823728_4","title":"Dynamic View Selection for OLAP","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Online analytical processing; Computer science; Materialized view; Data warehouse; Selection (genetic algorithm); Aggregate (composite); Task (project management); Set (abstract data type); Data mining; Information retrieval; Artificial intelligence; View","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":[0.0006912704,0.0007284022,0.0008169631,0.0008359983,0.0007249643,0.001984586,0.001567914,0.0005220952,0.009477097],"category_scores_gemma":[0.001795188,0.000545055,0.0005510708,0.001801235,0.0004557538,0.002791987,0.001789022,0.001401713,0.002362075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004915602,"about_ca_system_score_gemma":0.0005509854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001767277,"about_ca_topic_score_gemma":0.002468503,"domain_scores_codex":[0.9991856,0.0001465755,0.00005300958,0.0001305978,0.0003930832,0.00009115037],"domain_scores_gemma":[0.9990589,0.0002813352,0.00004050042,0.0003881814,0.0001685591,0.00006261031],"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":[0.0007000854,0.0001678887,0.001076637,0.0003229218,0.00008090454,0.0002730883,0.0001963542,0.02082762,0.0221835,0.05805948,0.05632967,0.8397818],"study_design_scores_gemma":[0.0001613577,0.0002360488,0.001244546,0.0001335565,0.0001088443,0.0009146277,0.0003166321,0.5869222,0.04426258,0.244911,0.120659,0.0001296381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01604042,0.002680492,0.9555698,0.0003052316,0.0002480552,0.0001014571,0.001058437,0.01248994,0.01150614],"genre_scores_gemma":[0.2798402,0.001698455,0.6980116,0.0002527032,0.0002393187,0.000156138,0.003788615,0.001887905,0.01412508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009477097,"threshold_uncertainty_score":0.03170407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136303530456793,"score_gpt":0.252280441725159,"score_spread":0.2409174064205911,"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."}}