{"id":"W2143104153","doi":"10.1109/tvlsi.2010.2062545","title":"Two-Stage, Pipelined Register Renaming","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Latency (audio); Register file; Parallel computing; Instructions per cycle; Logic synthesis; Computer architecture; Instruction set; Logic gate; Computer hardware; Central processing unit; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008521104,0.0003327587,0.0003428522,0.0004357569,0.0005392301,0.0005684866,0.0007975813,0.0002396844,0.00004907473],"category_scores_gemma":[0.00002360978,0.0003032976,0.0002073219,0.0006541492,0.0000607549,0.0008557503,0.000007464582,0.0007694286,0.0001504637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009706541,"about_ca_system_score_gemma":0.0001011994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001751481,"about_ca_topic_score_gemma":0.0004605887,"domain_scores_codex":[0.9974148,0.0002354202,0.0007126026,0.0006911601,0.0005093249,0.0004367497],"domain_scores_gemma":[0.9979076,0.0001523022,0.0002687107,0.001128703,0.0003684465,0.0001742684],"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":[0.0003308702,0.003347179,0.0002710531,0.000370824,0.0003527856,0.000114061,0.01063526,0.6933447,0.1016718,0.07587572,0.02862042,0.08506538],"study_design_scores_gemma":[0.0006527994,0.0001045427,0.00001779913,0.0001409096,0.00001410337,0.0000502142,0.0001823309,0.9527067,0.03514074,0.00008904949,0.01048906,0.0004117503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004395439,0.00002910048,0.984313,0.0003105013,0.004598673,0.0004550888,0.00003260861,0.001343388,0.004522227],"genre_scores_gemma":[0.9429358,0.00001617297,0.04609249,0.0002602579,0.0002109182,0.0001159133,0.00001345874,0.00003393331,0.01032107],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9385403,"threshold_uncertainty_score":0.9999419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509761356292194,"score_gpt":0.2679675271092134,"score_spread":0.2528699135462915,"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."}}