{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001381396,0.0002795076,0.0001512188,0.0003299152,0.0001671187,0.0002928494,0.0004180201,0.0002572886,0.001375627],"category_scores_gemma":[0.0003928411,0.0001345049,0.0001840596,0.0003172958,0.0001662254,0.0004735143,0.000337978,0.0004019887,0.000225964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003450921,"about_ca_system_score_gemma":0.0002230282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007851035,"about_ca_topic_score_gemma":0.001788243,"domain_scores_codex":[0.9998819,0.00002743297,0.000005436353,0.00002017501,0.000053364,0.00001167618],"domain_scores_gemma":[0.9998769,0.0000348334,0.00001406317,0.00003559632,0.00003313812,0.000005549144],"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":[0.0001025243,0.00003830036,0.0005034233,0.0001252186,0.00004993598,0.0001121979,0.00006770813,0.4413018,0.2044171,0.03593161,0.005371226,0.3119789],"study_design_scores_gemma":[0.00001075935,0.00007605817,0.0003470213,0.000006883243,0.00001479124,0.000119511,0.000007897467,0.9613639,0.01932971,0.007122703,0.01158411,0.00001669316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03762554,0.0009178228,0.9543895,0.00014622,0.0001211116,0.00002580465,0.00004292643,0.001063538,0.005667651],"genre_scores_gemma":[0.6065214,0.0008275021,0.3858438,0.0001408899,0.00007307502,0.00007681345,0.0001856966,0.000135412,0.00619535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001375627,"threshold_uncertainty_score":0.004601896,"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."}}