{"id":"W2593114675","doi":"","title":"Characterizing Database User’s Access Patterns","year":2008,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Database; Database testing; Database tuning; Workload; Database design; Access method; View; Data access; Set (abstract data type); Cache; Database server; Focus (optics); Online aggregation; Information retrieval; Web search query; Search engine; Web query classification; Operating system","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":[0.00266436,0.0004939309,0.0006277888,0.002904081,0.0005964632,0.001788963,0.0007592461,0.0005474428,0.0008607613],"category_scores_gemma":[0.01654136,0.0002948314,0.0002610937,0.002968696,0.0004599728,0.002932026,0.0009316946,0.0006757437,0.0003725897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006425685,"about_ca_system_score_gemma":0.0005686231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004095397,"about_ca_topic_score_gemma":0.004461884,"domain_scores_codex":[0.9953607,0.001393186,0.0004946873,0.0007793416,0.001674585,0.0002975741],"domain_scores_gemma":[0.9805514,0.008749569,0.00242891,0.003520876,0.004027396,0.0007219727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001934899,0.0007782173,0.6285358,0.0003352828,0.000334061,0.0005803281,0.003275855,0.02655575,0.03405648,0.006959144,0.005164808,0.2914894],"study_design_scores_gemma":[0.00005188666,0.0005647101,0.2378299,0.00005895272,0.0001790632,0.001719639,0.001840438,0.6910188,0.04085721,0.01481929,0.01092088,0.0001392414],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9297357,0.000295855,0.06323203,0.000323726,0.00002441407,0.0001314447,0.001442556,0.001418406,0.003395887],"genre_scores_gemma":[0.9850459,0.00008792717,0.01318183,0.00004869377,0.00001704791,0.00004633246,0.0009351505,0.000074076,0.0005630686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004095397,"threshold_uncertainty_score":0.01409066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175814229394269,"score_gpt":0.2905518657613022,"score_spread":0.1729704428218752,"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."}}