{"id":"W2131112324","doi":"10.1109/wcre.2009.51","title":"An Empirical Study on Inconsistent Changes to Code Clones at Release Level","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Software evolution; Computer science; Software; Code (set theory); Perspective (graphical); Software quality; Empirical research; Quality (philosophy); Software development; Software release life cycle; Software engineering; Open source software; Code review; Software construction; Programming language; Artificial intelligence; Statistics; Mathematics","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":[0.0003029744,0.000127998,0.0001353403,0.0001888868,0.00008961794,0.0001029286,0.0007775453,0.00003638003,0.00001584623],"category_scores_gemma":[0.0002994832,0.0001048969,0.00002464044,0.000417501,0.00001015737,0.0001018777,0.0002284357,0.0001153903,0.0002602708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001288948,"about_ca_system_score_gemma":0.00003195382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003232371,"about_ca_topic_score_gemma":0.0001867282,"domain_scores_codex":[0.9984977,0.00006899032,0.0001147232,0.0004728528,0.0005206651,0.0003251143],"domain_scores_gemma":[0.9984225,0.0003005312,0.00001231995,0.0008730614,0.00007017551,0.0003214141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003256415,0.009703424,0.5137629,0.00003086482,0.0001095675,0.001398208,0.02013496,0.008270896,0.01019499,0.005082655,0.1171442,0.3138417],"study_design_scores_gemma":[0.0003335282,0.003339522,0.9860802,0.000009723972,0.000002071228,0.00001160156,0.00007656431,0.005443809,0.002682019,0.0000708502,0.001726903,0.000223175],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9295655,0.0000102896,0.05864228,0.01060973,0.0001468265,0.0003487862,0.000002359122,0.0005270151,0.000147156],"genre_scores_gemma":[0.9847924,8.25323e-7,0.01191232,0.002425991,0.0000478629,0.0000225283,7.784952e-7,0.000008044549,0.0007893167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4723173,"threshold_uncertainty_score":0.4277572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130463340516356,"score_gpt":0.3774895446032434,"score_spread":0.2644432105516079,"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."}}