{"id":"W2018890516","doi":"10.1109/icsm.2011.6080794","title":"Late propagation in software clones","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"clone (Java method); Synchronizing; Software evolution; Biology; Software maintenance; Computer science; Software system; Software; Genetics; Programming language; Gene","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":[0.004070124,0.0006946129,0.0007019028,0.002758678,0.001121266,0.00207578,0.001415796,0.001805612,0.000874706],"category_scores_gemma":[0.0525745,0.0006992369,0.0008741799,0.001745157,0.002142861,0.004628657,0.002212302,0.001717822,0.0002291822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083332,"about_ca_system_score_gemma":0.0009872072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001579557,"about_ca_topic_score_gemma":0.001187049,"domain_scores_codex":[0.9926714,0.001596662,0.0006677342,0.001279299,0.003185423,0.0005994314],"domain_scores_gemma":[0.8912003,0.05828385,0.02042601,0.01594728,0.01274673,0.001395869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001212227,0.0004954016,0.3149875,0.001076895,0.000387954,0.005674618,0.008547806,0.05754091,0.08969303,0.08966798,0.002629186,0.4280867],"study_design_scores_gemma":[0.0002700226,0.003649514,0.1539567,0.0006456536,0.00109014,0.0310434,0.002418125,0.4180181,0.1607699,0.1872323,0.04046009,0.0004461108],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6542934,0.001773828,0.3376901,0.0003550551,0.00006811449,0.0002457336,0.0001099888,0.001292923,0.004170833],"genre_scores_gemma":[0.9499887,0.0003396389,0.04627832,0.0001795831,0.00005012747,0.0001017784,0.0001458639,0.0001804908,0.002735454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004070124,"threshold_uncertainty_score":0.02152508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403372786823052,"score_gpt":0.2487466589834545,"score_spread":0.214712931115224,"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."}}