{"id":"W4407128782","doi":"10.1109/jiot.2025.3538167","title":"OpenL3: Embedding Diverse Network Services into MANETs Using Multidimensional Identifier","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Beijing Jiaotong University; National Natural Science Foundation of China","keywords":"Computer science; Computer network; Identifier; Mobile ad hoc network; Embedding; Distributed computing; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002158934,0.000771994,0.0008675375,0.001357982,0.001098844,0.002639672,0.003071949,0.001167896,0.0023906],"category_scores_gemma":[0.002812982,0.0004237645,0.0007992145,0.001112893,0.001129873,0.005345005,0.007165638,0.001393369,0.001217328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084609,"about_ca_system_score_gemma":0.001240202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002454255,"about_ca_topic_score_gemma":0.001678713,"domain_scores_codex":[0.9983231,0.0004411626,0.000186934,0.0002495987,0.0005519179,0.0002471599],"domain_scores_gemma":[0.9980502,0.0003412299,0.0002713716,0.0007654618,0.0003066749,0.0002649814],"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":[0.001501078,0.0006601416,0.006738557,0.0008834251,0.0003006981,0.001829957,0.001529957,0.05147552,0.08841277,0.1697709,0.03825724,0.6386397],"study_design_scores_gemma":[0.0003020299,0.0009938565,0.002120859,0.000160909,0.0001744849,0.001343764,0.0006991833,0.6960735,0.0596334,0.06273892,0.1753578,0.0004012375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01997092,0.0005696195,0.9578354,0.0003889713,0.0002848164,0.0003233133,0.0002757246,0.01448992,0.005861308],"genre_scores_gemma":[0.5012457,0.000906485,0.485317,0.001001938,0.0002416271,0.0007975847,0.00187473,0.0007571495,0.007857715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003071949,"threshold_uncertainty_score":0.01141769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01394746298546801,"score_gpt":0.2902983454777164,"score_spread":0.2763508824922484,"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."}}