{"id":"W7039448333","doi":"","title":"A network impairment tool based on the IXDP425 network processor","year":2005,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Artificial neural network; Range (aeronautics); Key (lock); Process (computing); Pipeline (software)","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":[0.0008530274,0.001316897,0.0006518538,0.001156215,0.0004010773,0.0009725244,0.002057425,0.0004337785,0.02581415],"category_scores_gemma":[0.002832115,0.0005844317,0.0004425339,0.0008096969,0.0003423086,0.001441206,0.001265266,0.001183173,0.005012393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005803688,"about_ca_system_score_gemma":0.001028581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00264871,"about_ca_topic_score_gemma":0.002946293,"domain_scores_codex":[0.9992901,0.00008131393,0.00005164854,0.00008568223,0.0004003636,0.00009076417],"domain_scores_gemma":[0.9989842,0.0003688978,0.00008694566,0.0002428993,0.0002526732,0.00006444305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002379232,0.0005156399,0.008235535,0.0007847145,0.0001958383,0.0007831136,0.0004224087,0.09730453,0.05525607,0.0238444,0.1287953,0.6814833],"study_design_scores_gemma":[0.0004193936,0.0003196807,0.003026973,0.0001011741,0.0001402229,0.0005645189,0.0001126182,0.7409031,0.1104571,0.01157184,0.132281,0.0001022898],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02791969,0.0003103067,0.741699,0.0001528745,0.000149993,0.0004147994,0.001535175,0.2058441,0.02197406],"genre_scores_gemma":[0.44911,0.0006539641,0.4860054,0.0004701719,0.00007598831,0.0007521107,0.006798984,0.02031426,0.03581924],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02581415,"threshold_uncertainty_score":0.08635694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007394100107216,"score_gpt":0.1936051924103465,"score_spread":0.1835312514092744,"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."}}