{"id":"W2976097931","doi":"10.1109/mascots.2019.00030","title":"Characterization of IMAPS Email Traffic","year":2019,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cloud computing; Computer network; Enhanced Data Rates for GSM Evolution; Protocol (science); Transfer (computing); Telecommunications; 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":[0.0005589006,0.0006587062,0.0005460017,0.002818292,0.0006474541,0.0009020581,0.0007366451,0.0006293533,0.001125885],"category_scores_gemma":[0.002764489,0.0001574709,0.0001870303,0.002171274,0.000444351,0.00107003,0.0007042479,0.0005254175,0.0005928241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060837,"about_ca_system_score_gemma":0.0003664156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002859736,"about_ca_topic_score_gemma":0.001731243,"domain_scores_codex":[0.9991499,0.0001732718,0.00005353375,0.0001584438,0.0002919986,0.0001728105],"domain_scores_gemma":[0.9967526,0.001180234,0.0004445172,0.0003600477,0.001023684,0.0002389364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002441429,0.0009980757,0.336021,0.0004539159,0.0002582497,0.002839095,0.002282251,0.289905,0.2248713,0.01187651,0.01104118,0.1170119],"study_design_scores_gemma":[0.0000206299,0.0004793017,0.2028598,0.00005226739,0.00006534452,0.002174621,0.001892673,0.6770126,0.1051817,0.004086134,0.006056848,0.0001181056],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891371,0.0001409004,0.006070126,0.00006022687,0.00001435369,0.0000332102,0.001121578,0.0004886532,0.002933969],"genre_scores_gemma":[0.9970395,0.00009772542,0.001098205,0.00002785554,0.00001344103,0.00002731635,0.001072547,0.00004570542,0.0005776114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002859736,"threshold_uncertainty_score":0.007696986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007076561282301446,"score_gpt":0.1821681215418594,"score_spread":0.1750915602595579,"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."}}