{"id":"W1483906260","doi":"10.1007/978-3-540-45232-4_18","title":"Performance Analysis of a Software Design Using the UML Profile for Schedulability, Performance, and Time","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Unified Modeling Language; Scalability; Queueing theory; Applications of UML; Software design; Software; Distributed computing; Software engineering; Computer architecture; Programming language; Software development; Operating system; Computer network","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":[0.002973066,0.001252313,0.000587841,0.0022147,0.0005367803,0.001505558,0.0008874151,0.0006651015,0.003109223],"category_scores_gemma":[0.009762141,0.0006146008,0.00127369,0.0008240282,0.0004011253,0.001462178,0.0004909837,0.001049701,0.0009224759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493066,"about_ca_system_score_gemma":0.001571748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002908426,"about_ca_topic_score_gemma":0.001962927,"domain_scores_codex":[0.9974738,0.0007045339,0.0001723631,0.0001954557,0.001223339,0.0002304802],"domain_scores_gemma":[0.9931546,0.004288335,0.0005567037,0.0007107838,0.001173409,0.000116186],"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":[0.001679961,0.000517744,0.01039276,0.00123995,0.0002532948,0.0006454345,0.001324511,0.4205028,0.1488693,0.06223292,0.007097184,0.3452442],"study_design_scores_gemma":[0.00004843909,0.0004686613,0.002368301,0.0001145046,0.0001469654,0.0002687013,0.0000964205,0.9161198,0.06050377,0.01281596,0.006996272,0.00005216817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.164,0.0005329278,0.8193207,0.0003230725,0.00006833651,0.0002769417,0.0006517029,0.007246239,0.007580133],"genre_scores_gemma":[0.683374,0.0004033447,0.3089286,0.00008951532,0.00004646585,0.0003341087,0.001370481,0.001260958,0.004192515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003109223,"threshold_uncertainty_score":0.01572323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388922942065788,"score_gpt":0.2509928288620507,"score_spread":0.2271035994413928,"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."}}