{"id":"W2293611664","doi":"10.1049/el.2015.1024","title":"Improved adaptive routing for networks‐on‐chip","year":2015,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Routing (electronic design automation); Chip; Computer science; Adaptive routing; Computer network; Multipath routing; Electronic engineering; Computer architecture; Static routing; Routing protocol; Engineering; Telecommunications","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":[0.0006684735,0.0001618742,0.0001751481,0.00006062857,0.0001393612,0.0001640134,0.0005187775,0.0000659566,9.533498e-7],"category_scores_gemma":[0.00003891107,0.0001484812,0.0001097101,0.0002072247,0.00001576442,0.0002084877,0.00005956186,0.0002445125,0.00001172665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002578292,"about_ca_system_score_gemma":0.00007975366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001477982,"about_ca_topic_score_gemma":0.00002356932,"domain_scores_codex":[0.9985151,0.0000804611,0.0002276402,0.0003849723,0.0001563598,0.0006354355],"domain_scores_gemma":[0.9991649,0.0001458404,0.0001216305,0.0003656098,0.00009059164,0.0001114093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000230657,0.00007919206,0.00006499054,0.000008339759,0.0001781968,0.00001052435,0.001429879,0.1258525,0.00306859,0.7180965,0.128447,0.02253369],"study_design_scores_gemma":[0.0005786408,0.0005339446,0.000005822715,0.00001471845,0.000004515681,0.00001214083,0.00002750363,0.98125,0.0004836071,0.0007677042,0.0161148,0.000206527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005767863,0.0001846662,0.9878008,0.003642089,0.00147183,0.0003291906,6.263848e-7,0.0001662709,0.0006366902],"genre_scores_gemma":[0.987911,0.000002726468,0.00461724,0.006324223,0.0008427171,0.00007177433,0.000003094483,0.00002035865,0.000206795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9831836,"threshold_uncertainty_score":0.6054887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356071444585793,"score_gpt":0.2338608832634325,"score_spread":0.2103001688175746,"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."}}