{"id":"W3044418975","doi":"10.1051/epjconf/202024507026","title":"Web Proxy Auto Discovery for Dynamically Created Web Proxies","year":2020,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fermilab; Office of Science; University of Victoria; U.S. Department of Energy","keywords":"Computer science; Cache; Proxy (statistics); Operating system; World Wide Web; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00411479,0.0008203584,0.001492515,0.002475452,0.001590945,0.006462771,0.003454914,0.001760275,0.006059363],"category_scores_gemma":[0.008547494,0.001272057,0.0009812822,0.001865479,0.001414365,0.006346724,0.006222425,0.002432812,0.004532922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002506778,"about_ca_system_score_gemma":0.00290374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004278217,"about_ca_topic_score_gemma":0.005550157,"domain_scores_codex":[0.994743,0.0008701454,0.0005922685,0.0007356297,0.002300737,0.0007582204],"domain_scores_gemma":[0.9879847,0.001415528,0.0005584487,0.007538041,0.001733901,0.0007693393],"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":[0.00345609,0.001015512,0.01784416,0.0008618942,0.0003085027,0.002216852,0.001915458,0.02442019,0.06648065,0.1456212,0.1202829,0.6155767],"study_design_scores_gemma":[0.0003909915,0.0003017927,0.003904345,0.0002015475,0.0001511917,0.001340583,0.0003954805,0.3757643,0.1295002,0.02657509,0.4610433,0.0004311262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04357706,0.001459929,0.732544,0.000784273,0.0008122326,0.0008854694,0.001305985,0.1854521,0.03317906],"genre_scores_gemma":[0.492841,0.001011809,0.418503,0.0008830228,0.0004183171,0.0005426792,0.00533095,0.01086288,0.0696064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006462771,"threshold_uncertainty_score":0.02176136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02580766771574834,"score_gpt":0.2419968716353361,"score_spread":0.2161892039195877,"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."}}