{"id":"W2019509721","doi":"10.1016/j.jss.2006.07.019","title":"Interaction tree algorithms to extract effective architecture and layered performance models from traces","year":2006,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; IBM (Canada)","funders":"","keywords":"Computer science; Tracing; Asynchronous communication; TRACE (psycholinguistics); Tree (set theory); Architecture; Software architecture; Software; Reference architecture; Parallel computing; Pattern matching; Distributed computing; Theoretical computer science; 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":[0.0005169305,0.000183521,0.000408611,0.0001715046,0.0001468512,0.0002473845,0.0002459835,0.0001085606,9.936133e-7],"category_scores_gemma":[0.00003562671,0.0001254255,0.0000746315,0.0001625403,0.00002947513,0.001104417,0.00006725396,0.0002641881,0.000002300566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006300081,"about_ca_system_score_gemma":0.00003712742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004210281,"about_ca_topic_score_gemma":0.00002772259,"domain_scores_codex":[0.9985859,0.00009849364,0.0005287195,0.0002645382,0.0003297121,0.0001926045],"domain_scores_gemma":[0.9988142,0.0002766025,0.0003494246,0.0002202398,0.0002040566,0.000135465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001902183,0.0001491548,0.06218068,0.0004795771,0.0001293367,0.00006023526,0.004868083,0.05569753,0.0008218072,0.00009238652,0.0006794328,0.8746516],"study_design_scores_gemma":[0.003514529,0.002693827,0.7003534,0.003558445,0.0001021656,0.002958217,0.001050289,0.2704378,0.001392789,0.003754572,0.009018818,0.001165151],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6417398,0.002355993,0.3548851,0.00008354462,0.0006607228,0.0002067635,0.000005718265,0.00003548183,0.00002685511],"genre_scores_gemma":[0.9850869,0.00009369676,0.01435008,0.00002659192,0.0003761082,0.00001285056,0.00000101003,0.000009484068,0.00004330669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8734864,"threshold_uncertainty_score":0.5114705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009354810289471018,"score_gpt":0.2264522879345924,"score_spread":0.2170974776451213,"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."}}