{"id":"W1612325430","doi":"10.1109/inw.1997.603089","title":"Is there a future for global intelligent network standards?","year":2002,"lang":"en","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Standardization; Scope (computer science); Harmonization; Software deployment; Variety (cybernetics); Relevance (law); Telecommunications; Computer science; Global network; Service (business); Competition (biology); Engineering management; Business; Engineering; Marketing; Software engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003488631,0.0001877047,0.0001649592,0.00002047313,0.0001460202,0.000220132,0.0009760905,0.00006029637,0.001165959],"category_scores_gemma":[0.000005996901,0.000152382,0.0001479856,0.0004769963,0.00002016364,0.0001766211,0.0003156254,0.00006699441,0.0001236973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002736424,"about_ca_system_score_gemma":0.00002704096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007516251,"about_ca_topic_score_gemma":0.00004418386,"domain_scores_codex":[0.9982542,0.00003986195,0.0002371509,0.0004921195,0.0004559939,0.0005206452],"domain_scores_gemma":[0.9988634,0.00004076773,0.00007219878,0.0007861666,0.0001105845,0.0001268945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005062992,0.0000319717,0.0001619389,0.00001324264,0.0000364686,0.000006778584,0.00007976862,0.002115297,1.433729e-7,0.1621375,0.630202,0.2052099],"study_design_scores_gemma":[0.0002320142,0.0001185626,0.0000892069,0.00001394402,0.000008954951,0.00000173384,0.00002841031,0.2072823,0.00003364302,0.006639155,0.7853801,0.0001720374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001881685,0.00226437,0.9609944,0.005122398,0.001116829,0.0006911648,0.00001438615,0.000263778,0.02934454],"genre_scores_gemma":[0.4689426,0.002462559,0.4482502,0.04647181,0.006872674,0.0008124174,0.00001578183,0.000083061,0.02608896],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5127442,"threshold_uncertainty_score":0.9997471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188277813966058,"score_gpt":0.260789338942837,"score_spread":0.2389065608031764,"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."}}