{"id":"W4248071932","doi":"10.22215/etd/2014-10204","title":"Parallel Olap on Multi/Many-Core and Cloud Platforms","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data cube; Cloud computing; Parallel computing; Multi-core processor; Cube (algebra); Distributed computing; Data warehouse; Database; Data mining; 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":[0.0009364439,0.0006434344,0.0004626038,0.0006422263,0.0009011956,0.001971711,0.001124418,0.00040794,0.007420249],"category_scores_gemma":[0.001831831,0.000351,0.0005921007,0.001648324,0.0004613243,0.002277944,0.00139164,0.00126696,0.003018333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007629712,"about_ca_system_score_gemma":0.001772355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002867551,"about_ca_topic_score_gemma":0.003554554,"domain_scores_codex":[0.9989766,0.00009410075,0.00004452624,0.0001754402,0.0005340493,0.0001751964],"domain_scores_gemma":[0.9987873,0.0001866181,0.00006191145,0.000337857,0.0005010795,0.0001252664],"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":[0.0007543629,0.00045149,0.002272273,0.0009180929,0.0002219758,0.0004959063,0.0003872283,0.1244139,0.04697394,0.1589616,0.117162,0.5469872],"study_design_scores_gemma":[0.0001625409,0.0002385242,0.002849321,0.0002025057,0.00007943854,0.0003694116,0.0003881963,0.5121471,0.05073366,0.202673,0.2300689,0.00008754306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09268375,0.01538714,0.7438331,0.00633283,0.002094047,0.0006066968,0.001804742,0.007882195,0.1293755],"genre_scores_gemma":[0.375787,0.01156155,0.5545403,0.0008667563,0.0008622371,0.0004502985,0.004090745,0.001166846,0.05067433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007420249,"threshold_uncertainty_score":0.02482319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02843647196615171,"score_gpt":0.2734157038382292,"score_spread":0.2449792318720775,"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."}}