{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001565295,0.001235081,0.0005642386,0.001256985,0.0008051678,0.002126959,0.001799341,0.001079596,0.002056855],"category_scores_gemma":[0.01008641,0.001194197,0.00161266,0.0006430724,0.0009041546,0.002418157,0.001492814,0.001894878,0.0008839588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001731718,"about_ca_system_score_gemma":0.002820877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005447376,"about_ca_topic_score_gemma":0.007520316,"domain_scores_codex":[0.9983175,0.0004700686,0.0001150317,0.0001802957,0.0007885656,0.000128548],"domain_scores_gemma":[0.9939168,0.003105966,0.000623941,0.001336582,0.0008957786,0.0001209573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005333665,0.0001086635,0.002094673,0.000105629,0.00003958739,0.0001806999,0.0002533532,0.924903,0.005320451,0.0314858,0.001365106,0.03408973],"study_design_scores_gemma":[0.000006126618,0.000009620387,0.0001305652,0.000008849161,0.000007743191,0.00001941036,0.00001505291,0.9833753,0.002414645,0.01252063,0.001484379,0.000007691056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01732801,0.00005263413,0.9757172,0.0001253596,0.00001769204,0.0001145942,0.0003301602,0.004770339,0.001543854],"genre_scores_gemma":[0.432392,0.000236975,0.5616714,0.00005607625,0.00003393327,0.0005262365,0.001781665,0.001043086,0.002258651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005447376,"threshold_uncertainty_score":0.0125646,"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."}}