{"id":"W2889537237","doi":"10.14778/3229863.3236267","title":"ConTPL","year":2018,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences","keywords":"Differential privacy; Computer science; Bounding overwatch; Data stream mining; The Internet; Information privacy; Visualization; Data mining; Computer security; Artificial intelligence; World Wide Web","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":[0.003154729,0.001611259,0.0007434577,0.001429911,0.001022516,0.002957427,0.003562555,0.001784477,0.06985098],"category_scores_gemma":[0.01272136,0.0009655581,0.001053588,0.001005712,0.001090572,0.007169995,0.006411064,0.001855358,0.0451647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009997374,"about_ca_system_score_gemma":0.001339314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002182833,"about_ca_topic_score_gemma":0.002052711,"domain_scores_codex":[0.9969041,0.0005200449,0.0002718493,0.0009261864,0.001093068,0.0002846683],"domain_scores_gemma":[0.9926926,0.001700447,0.00039575,0.003765615,0.001189195,0.0002564516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002251018,0.0003746183,0.005330001,0.001097431,0.0001119366,0.001134457,0.001115564,0.004211862,0.01748929,0.06917938,0.4957761,0.4019282],"study_design_scores_gemma":[0.0002088672,0.0002891312,0.001910702,0.0001848651,0.00005289891,0.001355641,0.0001686457,0.05965608,0.03776848,0.04601018,0.852227,0.0001675837],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.008962355,0.0005409119,0.3858202,0.001209477,0.0004513497,0.0009106096,0.009979687,0.5288963,0.06322921],"genre_scores_gemma":[0.2824509,0.001261535,0.3308858,0.006546825,0.0006479101,0.002577367,0.0688686,0.1194517,0.1873094],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06985098,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235639165118382,"score_gpt":0.2541973367422107,"score_spread":0.2306334202303725,"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."}}