{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004773356,0.000394121,0.0003711733,0.0004006897,0.0006335297,0.0002438209,0.001005166,0.0001179984,0.0000588576],"category_scores_gemma":[0.000006118555,0.0004163248,0.0003371576,0.0009122945,0.00008037383,0.0003438907,0.00001248521,0.0002713346,0.00009532652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002985295,"about_ca_system_score_gemma":0.0001581871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006572774,"about_ca_topic_score_gemma":0.00002995596,"domain_scores_codex":[0.9971436,0.0002102159,0.0004982835,0.0009168312,0.0004378053,0.0007932477],"domain_scores_gemma":[0.9979584,0.0005544513,0.0002007127,0.0009049313,0.0001380512,0.000243493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002132988,0.0002918616,0.00002467306,0.0001178592,0.0001139696,0.000008365344,0.001458641,0.8708083,0.0005161972,0.001559247,0.0002201778,0.1248594],"study_design_scores_gemma":[0.001844313,0.0004373766,0.00001691495,0.00009985985,0.00004610645,0.00001188303,0.0003893222,0.9676114,0.006995121,0.0001796614,0.02184694,0.0005210965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02517706,0.00009378908,0.9702653,0.00007923051,0.001327061,0.002127399,0.00001742391,0.0005600755,0.0003526496],"genre_scores_gemma":[0.8874208,0.000042392,0.110072,0.0008091587,0.0001505794,0.0009773064,0.00000600983,0.00005463642,0.0004670749],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8622438,"threshold_uncertainty_score":0.9998289,"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."}}