{"id":"W2792146644","doi":"10.1002/spe.2567","title":"Hardware trace reconstruction of runtime compiled code","year":2018,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; TRACE (psycholinguistics); Executable; Tracing; Code (set theory); Kernel (algebra); Software; Linux kernel; Operating system; Granularity; Overhead (engineering); Source code; Just-in-time compilation; Parallel computing; Embedded system; Programming language; Virtual machine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000492859,0.0001578251,0.0002446042,0.00007340501,0.0002941343,0.0001009554,0.0004853216,0.0001022536,0.00004244195],"category_scores_gemma":[0.0009734778,0.0001357632,0.00005064919,0.0004117541,0.0004595131,0.002581418,0.0001974168,0.0001466098,0.00006024471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002832616,"about_ca_system_score_gemma":0.00009510026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009465669,"about_ca_topic_score_gemma":0.000009209189,"domain_scores_codex":[0.9984433,0.0001110152,0.0003841335,0.000488278,0.0003111194,0.0002621324],"domain_scores_gemma":[0.9980745,0.0003938784,0.0002928161,0.0006478159,0.0004845939,0.0001063643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004067678,0.0005034734,0.1415006,0.000388528,0.0001159907,0.00003064176,0.099603,0.00001635195,0.004074644,0.004165399,0.001999205,0.7471954],"study_design_scores_gemma":[0.007186356,0.006212506,0.137904,0.002005507,0.0002733333,0.00765987,0.04945811,0.02814628,0.1960707,0.007899394,0.5523663,0.004817606],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6441304,0.0007403997,0.3510794,0.0007235867,0.001425562,0.0003045242,0.000007284445,0.0003946778,0.001194183],"genre_scores_gemma":[0.8852958,0.0001272076,0.1140998,0.0002362754,0.0001210164,0.000026716,9.341642e-7,0.000007951479,0.00008427745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7423778,"threshold_uncertainty_score":0.5536262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505267496269081,"score_gpt":0.2835940215077755,"score_spread":0.2685413465450847,"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."}}