{"id":"W4415368556","doi":"10.1109/tccn.2025.3623369","title":"Internet of Agents: Fundamentals, Applications, and Challenges","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Orchestration; The Internet; Key (lock); Task (project management); Incentive; Trustworthiness; Virtual network","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":[0.0006777265,0.0003954734,0.0004609459,0.0005057778,0.0008000172,0.0002251339,0.001124065,0.0001526133,0.00003529744],"category_scores_gemma":[0.000003265041,0.0004604537,0.000130436,0.0009494968,0.0008014177,0.0002935828,0.0001694672,0.0005344085,0.000009729501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001245424,"about_ca_system_score_gemma":0.00009139422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006486015,"about_ca_topic_score_gemma":0.0001588137,"domain_scores_codex":[0.9972075,0.0005725802,0.0007875456,0.0007960654,0.0002397371,0.0003966345],"domain_scores_gemma":[0.9963111,0.00133686,0.0003596091,0.001607004,0.0002465076,0.0001389048],"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":[0.00004790502,0.0005823268,0.00007130604,0.0003214809,0.000490905,0.000001079133,0.0007440124,0.0001216489,0.000008579148,0.008421421,0.0001037631,0.9890856],"study_design_scores_gemma":[0.003325058,0.0008631492,0.001171005,0.008716524,0.001359495,0.00001591272,0.003135632,0.7649865,0.0009986424,0.002652785,0.211619,0.001156296],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004326284,0.1184843,0.8718893,0.001948073,0.0004562195,0.001467855,0.00003179185,0.00006905417,0.005220802],"genre_scores_gemma":[0.6501009,0.3465237,0.001932726,0.0005039553,0.00002965116,0.0005583469,0.000007693737,0.00001628771,0.0003267588],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9879293,"threshold_uncertainty_score":0.9997847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08745237762335628,"score_gpt":0.3008252907150247,"score_spread":0.2133729130916684,"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."}}