{"id":"W2956370112","doi":"10.1109/icc.2019.8761511","title":"Big Data Analytics for User Association Characterization in Large-Scale WiFi System","year":2019,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Big data; Analytics; Scale (ratio); Association (psychology); Data science; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007576789,0.00008394815,0.0001728661,0.00009252636,0.00003948707,0.0001404988,0.0005876368,0.0001007425,0.000008654591],"category_scores_gemma":[0.000007231422,0.00007677376,0.00002543643,0.0003467077,0.00000271113,0.0004976878,0.0002105174,0.00006530447,0.0000654032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001004942,"about_ca_system_score_gemma":0.0000653298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006115731,"about_ca_topic_score_gemma":0.00002915746,"domain_scores_codex":[0.9988971,0.0000354946,0.000270611,0.0003444196,0.000204364,0.0002480094],"domain_scores_gemma":[0.9988929,0.0001006646,0.0001543962,0.0007180601,0.00008588867,0.00004810664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007127386,0.0005628531,0.5706297,0.0004751665,0.0001529681,0.00001837759,0.001199912,0.0004657102,0.001276932,0.199492,0.02250578,0.2031492],"study_design_scores_gemma":[0.0004079477,0.00001876341,0.008060629,0.00002668018,0.000007410541,0.000001003162,0.00003898303,0.9698334,0.00001073129,0.00002912702,0.02145943,0.0001058951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01074583,0.00000492367,0.9848185,0.0003087264,0.001138815,0.0003096949,0.0001023173,0.00009066327,0.002480482],"genre_scores_gemma":[0.9744534,0.000008507413,0.01061697,0.0004022367,0.0002473897,0.000009886528,0.0008468915,0.00001040709,0.01340427],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9742016,"threshold_uncertainty_score":0.3130743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04513756551583335,"score_gpt":0.246274687998583,"score_spread":0.2011371224827496,"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."}}