{"id":"W1983065095","doi":"10.1023/b:supe.0000049326.25067.80","title":"Mobile Agent Connection Establishment and Management (CEMA)—Message Exchange for Pervasive Computing Environments","year":2004,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Egg Farmers of Canada","keywords":"Computer science; Ubiquitous computing; Context-aware pervasive systems; Mobile agent; Variety (cybernetics); Mobile computing; Distributed computing; Server; Mobile device; Computer network; Human–computer interaction; World Wide Web; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002342079,0.0006452629,0.0008663686,0.001304458,0.001968723,0.002697542,0.002017069,0.001830924,0.00379917],"category_scores_gemma":[0.00553654,0.0005948895,0.0003899221,0.0009444103,0.0008822175,0.002786654,0.002578363,0.002128213,0.002081816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005379764,"about_ca_system_score_gemma":0.001030956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001517009,"about_ca_topic_score_gemma":0.001802136,"domain_scores_codex":[0.9985152,0.0004785149,0.0001566755,0.0002318471,0.0004443081,0.0001735064],"domain_scores_gemma":[0.9962605,0.0009711909,0.0004247673,0.001486941,0.0004582723,0.0003983077],"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":[0.002204938,0.001057743,0.004034191,0.0004156536,0.0001687054,0.0009919199,0.001103534,0.01255381,0.06336897,0.1319074,0.03578076,0.7464124],"study_design_scores_gemma":[0.0004279263,0.001058212,0.003580889,0.0001584215,0.0002762803,0.001849131,0.0005145363,0.5678596,0.129875,0.0702218,0.223962,0.0002161123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02655062,0.0007628843,0.942739,0.0005614063,0.0005101124,0.000709752,0.0001532734,0.01402162,0.01399145],"genre_scores_gemma":[0.5175592,0.0006514905,0.4550747,0.0005127748,0.0004901086,0.0007473805,0.0006393065,0.0008799565,0.0234451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00379917,"threshold_uncertainty_score":0.0127095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665106662049321,"score_gpt":0.2348811964501188,"score_spread":0.2182301298296256,"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."}}