{"id":"W1972354026","doi":"10.1109/icdew.2013.6547437","title":"Client-centric OLAP on mobile devices","year":2013,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Simon Fraser University","funders":"","keywords":"Online analytical processing; Computer science; Mobile device; Client-side; Visualization; Software; Database; Operating system; Client–server model; Data visualization; Resource (disambiguation); Client; World Wide Web; Server; Data warehouse; Computer network; Data mining","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":[0.0008530754,0.0009285392,0.0009019343,0.0006009011,0.0007706232,0.001938045,0.002563179,0.0009531885,0.006487568],"category_scores_gemma":[0.002420858,0.0006994918,0.0003905151,0.001385238,0.0004511364,0.002050277,0.00158384,0.001072478,0.002685026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007926837,"about_ca_system_score_gemma":0.001192675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005463815,"about_ca_topic_score_gemma":0.004133244,"domain_scores_codex":[0.9983847,0.0002013337,0.00009785998,0.0003191265,0.0007366159,0.0002604334],"domain_scores_gemma":[0.996905,0.0005018208,0.0001815108,0.0009757261,0.001199704,0.0002362525],"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":[0.005742553,0.0009319635,0.01572101,0.002100857,0.0004362073,0.004467205,0.003043792,0.02834781,0.3507962,0.01545542,0.08677188,0.4861851],"study_design_scores_gemma":[0.000536262,0.001496706,0.02071877,0.000300382,0.0002549527,0.003534951,0.001886733,0.3668002,0.4706223,0.006977776,0.126425,0.0004458378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.426259,0.002105241,0.4588741,0.0008729996,0.000340796,0.001676724,0.002420759,0.07140888,0.03604141],"genre_scores_gemma":[0.8206987,0.0006996652,0.1574224,0.0003405885,0.00007222222,0.0004544431,0.001775884,0.001143503,0.01739268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006487568,"threshold_uncertainty_score":0.02170312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008882248168926079,"score_gpt":0.2173073683107213,"score_spread":0.2084251201417952,"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."}}