{"id":"W2149136155","doi":"10.1109/tmc.2003.1195148","title":"Policy-driven personalized multimedia services for mobile users","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Research Council Canada","keywords":"Computer science; Provisioning; Service (business); World Wide Web; Mobile device; The Internet; Service provider; Presentation (obstetrics); Negotiation; Mobile computing; Multimedia; Work (physics); Telecommunications; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0008004549,0.0002770326,0.0003085201,0.0003363392,0.0009349986,0.001543582,0.0007895126,0.001023833,0.002709089],"category_scores_gemma":[0.002113748,0.0002632632,0.0002326715,0.0003746936,0.0004050257,0.001484387,0.001059271,0.0008028112,0.001303329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008583656,"about_ca_system_score_gemma":0.001173689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003377556,"about_ca_topic_score_gemma":0.005072631,"domain_scores_codex":[0.9995165,0.00015577,0.00003010224,0.00005231103,0.0001729547,0.0000722825],"domain_scores_gemma":[0.9994982,0.0001513295,0.0000451911,0.0001161261,0.0001060943,0.00008303224],"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":[0.0009672833,0.0007638608,0.00461268,0.0003714596,0.00009895812,0.001386619,0.001897528,0.1483156,0.06202591,0.3082528,0.05182594,0.4194813],"study_design_scores_gemma":[0.0001050898,0.00009892937,0.001057734,0.00004702985,0.00004652304,0.0004075491,0.0004431915,0.7974789,0.01464523,0.07208713,0.113516,0.00006664646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1173852,0.002150411,0.7604097,0.005008852,0.0005359318,0.0006027118,0.0004265002,0.008797861,0.1046828],"genre_scores_gemma":[0.8768798,0.0008962739,0.09836297,0.0005867571,0.0002041725,0.0002712386,0.0003555832,0.0002515729,0.02219162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003377556,"threshold_uncertainty_score":0.009062827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151903350426769,"score_gpt":0.2673558545295681,"score_spread":0.2521655194868911,"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."}}