{"id":"W2049138229","doi":"10.1109/scam.2010.32","title":"Evaluating Code Clone Genealogies at Release Level: An Empirical Study","year":2010,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"clone (Java method); Code refactoring; Software evolution; Software maintenance; Java; Computer science; Software system; Source code; Programming language; Software; Biology; Genetics; Software construction; 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":[0.009486735,0.0002916279,0.0003518088,0.00377367,0.0007570924,0.001199803,0.0008999633,0.0007372156,0.0008781696],"category_scores_gemma":[0.1019051,0.0003034498,0.000386096,0.002702619,0.001360072,0.002634216,0.0009658898,0.001129595,0.0002439498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008792619,"about_ca_system_score_gemma":0.0005479115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003924025,"about_ca_topic_score_gemma":0.005858616,"domain_scores_codex":[0.9929542,0.002386467,0.0006699516,0.001266531,0.002435663,0.0002871254],"domain_scores_gemma":[0.7049593,0.210346,0.04340388,0.01665416,0.02221105,0.002425675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002032049,0.0002498178,0.9660653,0.00006907752,0.00008708665,0.0002710033,0.002805146,0.001863761,0.00178763,0.0003284197,0.0002646353,0.02600485],"study_design_scores_gemma":[0.00001869419,0.000630447,0.9805284,0.0000306625,0.00006448454,0.0006802146,0.002453932,0.01146079,0.002649103,0.0003617769,0.001086525,0.0000350335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983823,0.00005501294,0.00104008,0.00001990536,0.000001369751,0.00002920314,0.0001573314,0.00002131283,0.0002934044],"genre_scores_gemma":[0.9970903,0.00004487667,0.001922194,0.00001243575,0.000004020063,0.00004125907,0.0005839415,0.00001991831,0.0002810487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009486735,"threshold_uncertainty_score":0.05017126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2212351809237939,"score_gpt":0.4541855762864719,"score_spread":0.2329503953626781,"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."}}