{"id":"W2116783611","doi":"10.1109/ccece.1997.614832","title":"A Multimedia Transportable Agent System","year":2002,"lang":"en","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Multimedia; Mobile agent; Mobile computing; Multi-agent system; World Wide Web; Human–computer interaction; Distributed computing; Computer network; 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":[0.0008271813,0.0005791762,0.0005626061,0.0009490394,0.00121233,0.002463562,0.002055208,0.001414404,0.01311504],"category_scores_gemma":[0.001973243,0.0003634305,0.0004307946,0.0008345776,0.0004426955,0.00308961,0.001991851,0.00107674,0.004781515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006601778,"about_ca_system_score_gemma":0.001073029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001928046,"about_ca_topic_score_gemma":0.001174551,"domain_scores_codex":[0.9995089,0.00008718651,0.00006177805,0.00009557081,0.0001926201,0.00005396029],"domain_scores_gemma":[0.9992608,0.0001093649,0.00006452641,0.0001663338,0.0002038709,0.0001951057],"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":[0.002045982,0.0008468334,0.002689359,0.0009257942,0.0002410331,0.002798559,0.00104661,0.02024227,0.08627255,0.1017478,0.1475842,0.6335589],"study_design_scores_gemma":[0.000591621,0.0006153792,0.001166167,0.00016091,0.0003240326,0.001860737,0.0002091389,0.2535535,0.04305288,0.0284183,0.6698395,0.0002078362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0384653,0.001860316,0.7977352,0.001622718,0.0009586309,0.001505921,0.001771533,0.08840001,0.06768032],"genre_scores_gemma":[0.3738484,0.002227886,0.5427259,0.001248941,0.000684782,0.001628004,0.005367934,0.00256723,0.06970093],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01311504,"threshold_uncertainty_score":0.0438742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851774009760341,"score_gpt":0.1880342214813067,"score_spread":0.1695164813837033,"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."}}