{"id":"W2148758416","doi":"10.1109/iscc.2005.66","title":"Estimating the Task Route Reliability of Mobile Agent-Based Systems Using Monte Carlo Simulation","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Monte Carlo method; Robustness (evolution); Reliability (semiconductor); Task (project management); Distributed computing; Mobile agent; Mobile computing; Computer network; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002727391,0.0001172367,0.0001528897,0.00003757438,0.00006519067,0.00002992013,0.0001565093,0.00005317026,0.000006317429],"category_scores_gemma":[0.00008707733,0.00008888613,0.00003312718,0.0001403065,0.00003522367,0.0003317934,0.00002882061,0.00009944125,0.000001863124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649249,"about_ca_system_score_gemma":0.00001721738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001389731,"about_ca_topic_score_gemma":0.000007515598,"domain_scores_codex":[0.9991952,0.00002531068,0.0003427243,0.0001391528,0.0001507812,0.0001467892],"domain_scores_gemma":[0.9992639,0.0001271116,0.00008239027,0.0004237176,0.00007816448,0.00002464714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001996965,0.000008129641,0.0002171994,0.0001107725,0.000003663579,1.730411e-7,0.00006499236,0.9935095,0.002503278,0.000006253567,0.00003269701,0.003541386],"study_design_scores_gemma":[0.00007510502,0.000009312956,0.00003409996,0.00008118636,0.00001029254,6.270965e-7,0.00002661689,0.9924062,0.006347676,0.00002440593,0.0008876348,0.00009685524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2399315,0.0001873403,0.7588282,0.000005700396,0.00008295029,0.0002562084,0.00001902654,0.0005791042,0.0001099684],"genre_scores_gemma":[0.7314112,9.27245e-7,0.2684772,0.000008599928,0.00004455927,0.0000232668,0.000004237241,0.00002012988,0.000009892212],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4914797,"threshold_uncertainty_score":0.3624671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911685486716626,"score_gpt":0.2906178788985039,"score_spread":0.2715010240313376,"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."}}