{"id":"W2135712539","doi":"10.1109/mcom.2007.382663","title":"IP MULTIMEDIA SUBSYSTEM - IMS for Enterprises","year":2007,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; IP Multimedia Subsystem; Enterprise architecture; Architecture; Softswitch; Service (business); Relevance (law); Telecommunications; Quality of service; Telephony; Business","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":[0.001170762,0.0001763804,0.0001934732,0.0002049486,0.0002759419,0.0001265379,0.003997662,0.00005454586,0.00001355867],"category_scores_gemma":[0.00005629485,0.0001787863,0.0001155252,0.0005410026,0.000095547,0.000301358,0.0007089019,0.0001424837,0.0003527125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000155477,"about_ca_system_score_gemma":0.00004426496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001653738,"about_ca_topic_score_gemma":0.0002172316,"domain_scores_codex":[0.9984201,0.0001045611,0.0004883896,0.0003404205,0.0002311673,0.0004153826],"domain_scores_gemma":[0.9943149,0.0007980025,0.0001955027,0.004377273,0.0001804082,0.0001339078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008490423,0.001439917,0.002702887,0.0002406672,0.0003083721,0.00002942029,0.001911993,0.001660841,0.005238077,0.08401875,0.2983246,0.6040395],"study_design_scores_gemma":[0.001239512,0.000137882,0.00443111,0.00009085792,0.00004094846,0.00001050601,0.00005228755,0.2790657,0.001725177,0.0008189849,0.7119467,0.0004403261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001281063,0.0007738,0.9867429,0.00171333,0.00090952,0.001055989,0.000009213046,0.0003685683,0.007145579],"genre_scores_gemma":[0.6561925,0.0001977225,0.3405674,0.0007020569,0.0001875275,0.00039424,0.00004818594,0.00002694066,0.001683419],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6549114,"threshold_uncertainty_score":0.7428717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03699599833441108,"score_gpt":0.2971003217282988,"score_spread":0.2601043233938877,"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."}}