{"id":"W2784053634","doi":"10.1145/3164135.3164139","title":"The ubiquity of large graphs and surprising challenges of graph processing","year":2017,"lang":"en","type":"article","venue":"Very Large Data Bases","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scalability; Suite; Visualization; Graph; Software; Data science; Call graph; Theoretical computer science; Data visualization; World Wide Web; Data mining; Programming language; Database","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":[0.01665007,0.0005647455,0.0006027501,0.00383631,0.001943211,0.005126248,0.001875094,0.002001041,0.002525181],"category_scores_gemma":[0.09797047,0.0009414402,0.0007068611,0.005139848,0.003871364,0.01391352,0.003082968,0.002705615,0.0007653342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00132996,"about_ca_system_score_gemma":0.001086869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0014195,"about_ca_topic_score_gemma":0.002927428,"domain_scores_codex":[0.981712,0.00960679,0.0007187931,0.002233666,0.005285201,0.0004436028],"domain_scores_gemma":[0.7985132,0.1728275,0.006979656,0.01091679,0.00853043,0.002232422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003794027,0.0001734384,0.0684664,0.007079237,0.0003123878,0.003048769,0.09182882,0.01105089,0.01797997,0.1034337,0.05955552,0.6366914],"study_design_scores_gemma":[0.00005084462,0.0003356877,0.05832219,0.0017204,0.0001243535,0.009872593,0.08603596,0.03705144,0.01026969,0.317145,0.4786808,0.0003910153],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5417594,0.02318249,0.3535745,0.0526655,0.0007267293,0.0003623113,0.001896974,0.003624843,0.02220725],"genre_scores_gemma":[0.7660667,0.01230464,0.2094789,0.003797355,0.0008154043,0.0002850702,0.001863942,0.002015052,0.003373004],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01665007,"threshold_uncertainty_score":0.08805501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07621659304314052,"score_gpt":0.3534706649777041,"score_spread":0.2772540719345635,"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."}}