{"id":"W7143321693","doi":"10.1109/emergin67762.2025.11450575","title":"A Comprehensive Study and Implementation of Agentic AI via MCP Servers","year":2025,"lang":"","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Server; Focus (optics); Key (lock); Troubleshooting; The Internet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003689189,0.0003397702,0.0004602433,0.0004127694,0.000216827,0.0002517948,0.0007441932,0.00004933068,0.0004599307],"category_scores_gemma":[0.000003940813,0.0003574661,0.0001096045,0.001401578,0.0001073957,0.0004491817,0.001708862,0.0001464993,0.00002182088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001550859,"about_ca_system_score_gemma":0.0001594751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001554098,"about_ca_topic_score_gemma":0.0006299639,"domain_scores_codex":[0.9967816,0.0003950788,0.0009025193,0.0009266778,0.0005227441,0.0004713751],"domain_scores_gemma":[0.9981811,0.0001323779,0.0002890511,0.001003909,0.000277695,0.000115867],"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":[0.00009549401,0.001749207,0.07496071,0.001559055,0.002209259,0.0001152727,0.008103609,0.004352886,0.0009255338,0.01921978,0.02252699,0.8641822],"study_design_scores_gemma":[0.008721647,0.002596338,0.4552006,0.0002149711,0.0008948605,0.000003266285,0.0178485,0.5016612,0.002888658,0.001582942,0.007563049,0.0008240195],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.546725,0.0004885302,0.4455885,0.001469282,0.001014715,0.003948634,0.000004022929,0.00006842423,0.0006928602],"genre_scores_gemma":[0.9950225,0.000102552,0.001639321,0.002180584,0.00002226948,0.00009077891,0.000004296256,0.00001069252,0.000926947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8633582,"threshold_uncertainty_score":0.9998877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396062425421813,"score_gpt":0.3091242298654012,"score_spread":0.295163605611183,"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."}}