{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004091319,0.001202771,0.001045603,0.003354929,0.001665781,0.002779095,0.001867761,0.0008409671,0.002472141],"category_scores_gemma":[0.016255,0.0004057182,0.000589411,0.006762214,0.001131789,0.004791019,0.001627692,0.001021646,0.0007092428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00229832,"about_ca_system_score_gemma":0.001925491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008913552,"about_ca_topic_score_gemma":0.003083537,"domain_scores_codex":[0.9929364,0.001506792,0.0006998139,0.0009741997,0.002930681,0.0009521318],"domain_scores_gemma":[0.9811369,0.007803862,0.001500256,0.002222727,0.005681269,0.001654997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003374844,0.00202374,0.1182123,0.004096908,0.0009253561,0.001232121,0.002928767,0.5226623,0.03331081,0.04129516,0.0845366,0.1854011],"study_design_scores_gemma":[0.0001494449,0.001772913,0.05208088,0.0001596325,0.0001553419,0.000738452,0.002639315,0.8829492,0.01926734,0.01453953,0.02541662,0.0001312819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9257112,0.008213595,0.02751197,0.002632105,0.000603299,0.0004460795,0.00572413,0.003801706,0.02535585],"genre_scores_gemma":[0.9831007,0.001230033,0.009635158,0.0001380627,0.0001588676,0.0001283563,0.004166683,0.0002192168,0.001223057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008913552,"threshold_uncertainty_score":0.02163726,"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."}}