{"id":"W2006834218","doi":"10.5555/2486788.2487008","title":"Supporting maintenance tasks on transformational code generation environments","year":2013,"lang":"en","type":"article","venue":"International Conference on Software Engineering","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Code refactoring; Model transformation; Computer science; Software engineering; Executable; Transformational leadership; Software development; Code generation; Transformation (genetics); Software maintenance; Model-driven architecture; Software system; Field (mathematics); Separation of concerns; Software; Programming language; Artificial intelligence; Key (lock)","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"],"consensus_categories":[],"category_scores_codex":[0.0001839902,0.0002816821,0.0001723069,0.0002460408,0.00006881588,0.0002548047,0.0009291439,0.0001027178,0.0002246905],"category_scores_gemma":[0.00006128529,0.0002891221,0.00008266095,0.0001137637,0.00001942485,0.0009286662,0.00009467468,0.000316598,0.0002838221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002412211,"about_ca_system_score_gemma":0.00003683702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001059754,"about_ca_topic_score_gemma":8.725762e-7,"domain_scores_codex":[0.9980936,0.00001813249,0.0004144857,0.0004492277,0.0006533086,0.0003712476],"domain_scores_gemma":[0.9991871,0.00005946405,0.0001132568,0.0003993495,0.000117953,0.0001229525],"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":[0.000006643504,0.0001137083,0.0003990809,0.00002048527,0.00007268042,0.00001965333,0.0005559023,0.1294276,0.01151303,0.7865757,0.002678406,0.06861708],"study_design_scores_gemma":[0.0002595251,0.00009023859,0.001830579,0.0001244875,0.000002427797,0.00001693101,0.000003102456,0.9670915,0.008526772,0.0006167007,0.02104944,0.0003883231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01208261,0.000005455499,0.9851213,0.0006400496,0.0006811846,0.0002777106,0.00002617331,0.0007786231,0.0003868801],"genre_scores_gemma":[0.6856053,0.00001486191,0.3133381,0.0003158693,0.0001267173,0.0001964631,0.0000612363,0.00002613521,0.0003153289],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8376639,"threshold_uncertainty_score":0.9999561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672411748924588,"score_gpt":0.2606567155084247,"score_spread":0.2339325980191788,"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."}}