{"id":"W2149698371","doi":"10.5555/776261.776291","title":"Dynamic profiling and trace cache generation","year":2003,"lang":"en","type":"article","venue":"Symposium on Code Generation and Optimization","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Profiling (computer programming); Java; Cache; TRACE (psycholinguistics); Call graph; Parallel computing; Distributed computing; Operating system","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":[0.001313571,0.0007443992,0.0006326158,0.001732388,0.0004933905,0.001270777,0.001615587,0.0007732047,0.001377296],"category_scores_gemma":[0.01245511,0.000527924,0.0003485032,0.001594963,0.0005423829,0.001847473,0.0009954671,0.001024233,0.0006296614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007574723,"about_ca_system_score_gemma":0.001281865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130548,"about_ca_topic_score_gemma":0.002426646,"domain_scores_codex":[0.997433,0.0006004789,0.0001629598,0.000394964,0.001177331,0.000231169],"domain_scores_gemma":[0.9914506,0.002863656,0.0008704339,0.003001312,0.001589398,0.0002245264],"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":[0.0009872651,0.0004893816,0.02875806,0.0002795551,0.0001043831,0.0005094858,0.0009534028,0.08693806,0.1210879,0.02588025,0.009988689,0.7240236],"study_design_scores_gemma":[0.00004652152,0.0002444104,0.004071832,0.00003554162,0.00004157368,0.0004150596,0.0001217071,0.8129416,0.1568299,0.01328469,0.01189717,0.00007014846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1108411,0.0002311697,0.8574744,0.0002666567,0.00005546406,0.0001844215,0.0005178279,0.02778229,0.00264672],"genre_scores_gemma":[0.6809193,0.0001596765,0.3126243,0.0001489854,0.00003157178,0.0003190649,0.001321875,0.001610605,0.002864538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002130548,"threshold_uncertainty_score":0.006946862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063276269422019,"score_gpt":0.2551050567654122,"score_spread":0.2344722940711921,"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."}}