{"id":"W2510761896","doi":"10.18293/seke2016-142","title":"Cross-Model Traceability for Coupled Transformation of Software and Performance Models","year":2016,"lang":"en","type":"article","venue":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metamodeling; Traceability; Computer science; Model transformation; Unified Modeling Language; Abstraction; Transformation (genetics); Software engineering; Distributed computing; Programming language; Software; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01005516,0.00130598,0.0008185051,0.002098213,0.001271774,0.003879032,0.002530053,0.002130006,0.004770138],"category_scores_gemma":[0.03412806,0.001156534,0.002928692,0.001906333,0.002881867,0.007924127,0.007917027,0.00477529,0.001150097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002494571,"about_ca_system_score_gemma":0.003453069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00651978,"about_ca_topic_score_gemma":0.004455952,"domain_scores_codex":[0.9892525,0.004104948,0.001125996,0.001604568,0.003394844,0.0005171464],"domain_scores_gemma":[0.9806147,0.006642125,0.001499339,0.008817812,0.0021359,0.0002901322],"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":[0.0001829273,0.0002760114,0.003087525,0.0004084274,0.0001942128,0.0009022992,0.002976859,0.1134904,0.01399093,0.7461597,0.001779277,0.1165514],"study_design_scores_gemma":[0.00005671438,0.0002071377,0.000812281,0.0003097739,0.0001833462,0.0004233581,0.0003517465,0.4493775,0.0331298,0.4663962,0.04862672,0.0001253791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003214332,0.00003872701,0.9939156,0.00009762849,0.00002741101,0.0000947559,0.00004032929,0.001044031,0.001527193],"genre_scores_gemma":[0.2337915,0.0003369761,0.7575712,0.0002870395,0.00006429569,0.0008783935,0.0006652392,0.00162498,0.004780422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01005516,"threshold_uncertainty_score":0.05317748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02281103675117123,"score_gpt":0.2443031053994861,"score_spread":0.2214920686483149,"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."}}