{"id":"W2538602044","doi":"10.1109/icm.2010.5696215","title":"A hardware/software co-design architecture for packet classification","year":2010,"lang":"en","type":"article","venue":"","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Header; Speedup; Network packet; Network processor; Preprocessor; Software; Processing delay; Packet processing; Parallel computing; Algorithm; Artificial intelligence; Computer network; Transmission delay; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003252733,0.000114154,0.00009890625,0.00007153002,0.0002005962,0.0002671584,0.0004889293,0.0001005848,0.0000209685],"category_scores_gemma":[0.0001360434,0.00009389102,0.00004491684,0.0002370212,0.00003552215,0.0002732573,0.00002938311,0.0001596995,0.00002615116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001038311,"about_ca_system_score_gemma":0.00009050137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001605044,"about_ca_topic_score_gemma":0.000008609928,"domain_scores_codex":[0.9991143,0.00003334433,0.0001454235,0.0003399811,0.0001468985,0.0002201],"domain_scores_gemma":[0.9990714,0.000198405,0.00007998426,0.0004273817,0.0001430944,0.00007974809],"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":[0.00004368823,0.0001295435,0.0005412996,0.00006335293,0.00002210849,0.000001766518,0.001002093,0.006425926,0.005871824,0.06703165,0.104432,0.8144347],"study_design_scores_gemma":[0.0007326624,0.0001646587,0.000999184,0.00002511281,0.00001248625,0.00002611678,0.00002055896,0.8620642,0.009503109,0.05042622,0.07554521,0.0004805149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002729446,0.00001394432,0.9957307,0.001492523,0.0003384897,0.0002795929,0.000002448951,0.0005034812,0.001365874],"genre_scores_gemma":[0.06163977,0.000003155806,0.9363265,0.0004854495,0.0001768988,0.0000723939,0.00002456154,0.00001344455,0.001257834],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8556383,"threshold_uncertainty_score":0.3828765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034957808487861,"score_gpt":0.2765447089798274,"score_spread":0.2461951308949488,"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."}}