{"id":"W2129173237","doi":"10.1109/ccgrid.2012.138","title":"Automated Construction of Performance Models for High Performance Distributed Applications","year":2012,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Concurrency; TRACE (psycholinguistics); Asynchronous communication; Distributed computing; Queueing theory; Fork (system call); Construct (python library); Task (project management); Process (computing); Software performance testing; Performance prediction; Software; Message queue; Software engineering; Software development; Operating system; Computer network; Programming language; Software construction","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":[0.0003938023,0.0001341436,0.0002084492,0.00007579316,0.0001839406,0.00002227201,0.0004328857,0.00009387726,0.000007432816],"category_scores_gemma":[0.000009649862,0.0001071425,0.00005329763,0.000449943,0.00009013031,0.001556831,0.0000859895,0.00006370563,0.00002232839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005698233,"about_ca_system_score_gemma":0.00006344368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000950732,"about_ca_topic_score_gemma":2.8036e-7,"domain_scores_codex":[0.9988157,0.0000184699,0.0004003835,0.0002232507,0.0001974913,0.0003446999],"domain_scores_gemma":[0.9988305,0.000071895,0.0001683325,0.0005788796,0.0002630892,0.00008728467],"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":[0.00009780012,0.0008295152,0.2166701,0.002601405,0.0001502744,7.923727e-8,0.001091082,0.0314927,0.001241814,0.4444327,0.001686943,0.2997056],"study_design_scores_gemma":[0.0004150603,0.00009374834,0.02725247,0.00002833068,0.00001220762,0.00001594463,0.00002353298,0.9548291,0.01531584,0.0005428798,0.001271528,0.0001993736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2931456,0.00003930262,0.7049798,0.00004976634,0.0002783951,0.0004970375,0.00001849472,0.0006064522,0.0003851378],"genre_scores_gemma":[0.8814479,0.00003477575,0.1180649,0.00001933495,0.00007038657,0.0002903019,0.00003248297,0.000006594253,0.00003331432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9233364,"threshold_uncertainty_score":0.4369146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364188393610696,"score_gpt":0.2374163846581493,"score_spread":0.2237745007220424,"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."}}