{"id":"W2980787539","doi":"10.22215/etd/2019-13518","title":"Incremental Change Propagation from Software to Performance Models","year":2019,"lang":"en","type":"dissertation","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; Metamodeling; Model transformation; Unified Modeling Language; Transformation (genetics); Software development; Software engineering; Software; Traceability; Data mining; Programming language; Artificial intelligence; Consistency (knowledge bases)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002438459,0.0003497794,0.0003802866,0.0001984203,0.0001433658,0.0001652006,0.001102702,0.0003215238,0.00006755535],"category_scores_gemma":[0.00001936812,0.0002879376,0.000106317,0.0003639217,0.000007996891,0.00171262,0.0001688654,0.0002432305,0.001314328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001941286,"about_ca_system_score_gemma":0.0001734891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007547176,"about_ca_topic_score_gemma":0.0001408543,"domain_scores_codex":[0.9976753,0.00003929508,0.0004381345,0.0008261413,0.0006751719,0.0003459799],"domain_scores_gemma":[0.9983829,0.00004178372,0.0001974625,0.001017827,0.0002395204,0.0001204518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002345987,0.0003118841,0.0233526,0.002482739,0.0001728881,0.000006658617,0.03088296,0.00116985,0.001106379,0.001444785,0.004662024,0.9341726],"study_design_scores_gemma":[0.002514574,0.001752056,0.2596068,0.004596113,0.000147021,0.00001302771,0.001950253,0.6539124,0.06244546,0.002633756,0.004844349,0.005584154],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8985019,0.000201681,0.09030786,0.0001028417,0.004410591,0.002269282,0.00002853122,0.0007148553,0.003462455],"genre_scores_gemma":[0.9750236,0.00005666242,0.01850495,0.0004876516,0.0003233849,0.0004781173,0.0007804699,0.00003818833,0.004307001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9285885,"threshold_uncertainty_score":0.9999573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02908444690560083,"score_gpt":0.2520140464699905,"score_spread":0.2229295995643897,"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."}}