{"id":"W2753088425","doi":"10.14778/3137628.3137637","title":"I've seen \"enough\"","year":2017,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Usability; Sampling (signal processing); Interactivity; Data mining; Context (archaeology); Speedup; Creative visualization; Data visualization; Sample (material); Machine learning; Data science; Human–computer interaction; World Wide Web; Computer vision; Parallel computing","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":[0.0009754866,0.0009650324,0.0005914138,0.0009314922,0.0007946183,0.002523969,0.0007530689,0.001266006,0.02682389],"category_scores_gemma":[0.00956004,0.0003808057,0.0008603484,0.001274322,0.0005352107,0.00361291,0.002032952,0.001750222,0.006387574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003859253,"about_ca_system_score_gemma":0.0006016992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002678554,"about_ca_topic_score_gemma":0.005868556,"domain_scores_codex":[0.9995092,0.0001106601,0.00002473123,0.0001317358,0.00015736,0.00006624041],"domain_scores_gemma":[0.9974217,0.001191869,0.0002038446,0.0003826995,0.0005603622,0.0002395311],"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":[0.001715698,0.0001812942,0.02916214,0.001380943,0.0002444344,0.0009528795,0.004449212,0.006648702,0.02038911,0.01832489,0.3134094,0.6031414],"study_design_scores_gemma":[0.0003079977,0.0007045291,0.05250166,0.001743806,0.0006588858,0.003715289,0.00658567,0.1168049,0.03731681,0.1072575,0.6718316,0.0005712713],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1722456,0.005928044,0.5790727,0.02959044,0.005989013,0.0007389318,0.02434983,0.06834939,0.1137361],"genre_scores_gemma":[0.5284244,0.003471813,0.420492,0.003958081,0.0008539901,0.0005105298,0.01106728,0.005699235,0.02552272],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02682389,"threshold_uncertainty_score":0.08973491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02677895040393549,"score_gpt":0.2904718505086095,"score_spread":0.2636929001046739,"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."}}