{"id":"W2095232189","doi":"10.1109/ispass.2013.6557159","title":"QTrace: An interface for customizable full system instrumentation","year":2013,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"x86; Instrumentation (computer programming); Computer science; Operating system; Embedded system; Interface (matter); Source code; Architecture; Open source; Code (set theory); Computer architecture; Software; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.0001776236,0.00008531161,0.00009378455,0.00007059741,0.0001097481,0.0002996011,0.000466332,0.00004404853,0.00001937017],"category_scores_gemma":[0.000008786873,0.0000747865,0.00002814119,0.0001345048,0.00001026634,0.0009465748,0.00007356199,0.00003855774,0.00008221722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000498792,"about_ca_system_score_gemma":0.00002237801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007180372,"about_ca_topic_score_gemma":0.000002572127,"domain_scores_codex":[0.9992778,0.00003774875,0.0001827293,0.0002433057,0.00009250356,0.0001659655],"domain_scores_gemma":[0.9993953,0.00003122567,0.00007016976,0.0002994826,0.0001381122,0.00006572057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003946291,0.0003515901,0.0002713759,0.0002809633,0.00005923486,0.000001402044,0.002527455,0.1414838,0.009687329,0.5192252,0.1010142,0.225058],"study_design_scores_gemma":[0.0002059587,0.0001321967,0.00003535094,0.000013588,0.000001485875,0.000006395879,0.0001017175,0.9878268,0.01011251,0.0006514715,0.0008042458,0.0001083229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009007176,0.00001253933,0.984011,0.0002639729,0.0001728371,0.000426935,4.818477e-7,0.001225755,0.004879311],"genre_scores_gemma":[0.5095068,9.760022e-7,0.4897291,0.00007703208,0.00001814293,0.00006148304,0.000002415333,0.000004519517,0.0005995301],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.846343,"threshold_uncertainty_score":0.3049705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01481652300712677,"score_gpt":0.2709783376440896,"score_spread":0.2561618146369629,"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."}}