{"id":"W2907216425","doi":"10.1145/3282834.3282841","title":"A Performance Study of Big Spatial Data Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Big data; Computer science; Scalability; SPARK (programming language); Spatial analysis; Benchmark (surveying); Field (mathematics); Variety (cybernetics); Volume (thermodynamics); Computer data storage; Data science; Database; Data mining; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002949111,0.00005510381,0.00008520193,0.00005937464,0.00005005386,0.0001058142,0.002314543,0.000008829204,0.00001012404],"category_scores_gemma":[0.000006338462,0.00004156011,0.000005157462,0.0002206749,0.0000236439,0.0007101265,0.001872683,0.00002270302,0.00009023483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003351171,"about_ca_system_score_gemma":0.0000113876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007522446,"about_ca_topic_score_gemma":0.0001222042,"domain_scores_codex":[0.9992254,0.00002039899,0.0001468167,0.000270376,0.0002257637,0.0001111823],"domain_scores_gemma":[0.9982825,0.00000971046,0.00005199391,0.001589522,0.00004358209,0.00002270973],"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":[0.00001200058,0.001093521,0.02973078,0.00008793162,0.0001110994,0.00001091422,0.001454008,0.00002265128,0.00005487931,0.007716519,0.02421241,0.9354933],"study_design_scores_gemma":[0.000360594,0.0005845972,0.009184254,0.000009642752,0.000006638659,0.000001038532,0.000204209,0.9804061,0.00005434112,0.000005886326,0.009094333,0.00008833393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2708824,0.00001330719,0.6988915,0.00005541558,0.002048093,0.0004269952,0.00001038819,0.0001483699,0.02752356],"genre_scores_gemma":[0.9957062,0.000002613298,0.003017965,0.00001828912,0.0002205437,0.00000295703,0.000007345835,0.000002322278,0.00102178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9803835,"threshold_uncertainty_score":0.4301036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0771246113023431,"score_gpt":0.2765820328687794,"score_spread":0.1994574215664363,"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."}}