{"id":"W2098010876","doi":"10.1109/icpp.2007.21","title":"Automatic Trace-Based Parallelization of Java Programs","year":2007,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Parallel Processing","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Automatic parallelization; Java; TRACE (psycholinguistics); Parallel computing; Suite; Benchmark (surveying); Parallelism (grammar); Programming language; Compiler","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":[0.001436818,0.001231992,0.0007155931,0.001069514,0.0005727867,0.001095298,0.002112093,0.0005230697,0.002128895],"category_scores_gemma":[0.007778254,0.0005500664,0.0005315786,0.0007405116,0.0007521255,0.001696607,0.001131255,0.001181927,0.0007493283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006797619,"about_ca_system_score_gemma":0.001823529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004061048,"about_ca_topic_score_gemma":0.003980175,"domain_scores_codex":[0.9980906,0.0004813012,0.0001407917,0.000377653,0.000753957,0.0001557439],"domain_scores_gemma":[0.9945236,0.001886722,0.0004288933,0.001640932,0.001347693,0.0001720463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009965806,0.0007558304,0.005248914,0.0003665439,0.0001181242,0.0002565506,0.0007024705,0.1225866,0.1329928,0.01025756,0.007749965,0.717968],"study_design_scores_gemma":[0.00009235062,0.0001409162,0.0007563912,0.00001478274,0.00002193264,0.00008153023,0.00006708821,0.8733715,0.1128725,0.008419332,0.004126419,0.00003517477],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04961057,0.00006814481,0.9147135,0.0001225955,0.00003702581,0.0001786354,0.0001416446,0.033724,0.001403832],"genre_scores_gemma":[0.4059158,0.0001096911,0.5879166,0.00009728648,0.00003226934,0.0003052857,0.0009510496,0.002651951,0.002020081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004061048,"threshold_uncertainty_score":0.00807482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.041380483445933,"score_gpt":0.2954646394018596,"score_spread":0.2540841559559266,"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."}}