{"id":"W2146624380","doi":"10.1007/s10115-006-0024-8","title":"Answering ad hoc aggregate queries from data streams using prefix aggregate trees","year":2006,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"National University of Singapore","keywords":"Computer science; Aggregate (composite); Scalability; Trie; Prefix; Data stream mining; Data stream; Data warehouse; Data mining; Database; Data structure; 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":[0.004178346,0.001166741,0.002864933,0.002694424,0.00142303,0.00483431,0.001934486,0.002208847,0.001786571],"category_scores_gemma":[0.01457525,0.001020866,0.001365311,0.00531787,0.0009500993,0.0104935,0.003330774,0.002215965,0.0007695121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008822839,"about_ca_system_score_gemma":0.001576486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002518015,"about_ca_topic_score_gemma":0.003854693,"domain_scores_codex":[0.9953167,0.0006835784,0.0007602776,0.0007508041,0.002171529,0.0003169777],"domain_scores_gemma":[0.9871508,0.008255642,0.0008368188,0.001905022,0.001480398,0.0003713039],"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":[0.003634849,0.001109498,0.02098014,0.001498966,0.0009109913,0.001601667,0.002382696,0.1981337,0.06432297,0.04017056,0.02602844,0.6392255],"study_design_scores_gemma":[0.00009372772,0.0001655304,0.001013715,0.00003498153,0.0001558786,0.0003163383,0.0006740466,0.9235201,0.01510627,0.05393293,0.00494981,0.00003652437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1131701,0.001227729,0.8752964,0.0009100508,0.0001874523,0.0003057632,0.002067661,0.005271998,0.001562795],"genre_scores_gemma":[0.5105448,0.00119023,0.4768758,0.0003918043,0.0004361965,0.0002976091,0.007826624,0.0004121751,0.002024767],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00483431,"threshold_uncertainty_score":0.02209747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02539816418324298,"score_gpt":0.257263077859474,"score_spread":0.231864913676231,"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."}}