{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001263183,0.0001315262,0.0001378316,0.0001104504,0.0001662262,0.0001733341,0.001216079,0.0000639721,0.0001035301],"category_scores_gemma":[0.002053407,0.0001104389,0.00003224119,0.0003734059,0.00004082676,0.0003268486,0.0009185075,0.0003615831,0.0002146019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005891181,"about_ca_system_score_gemma":0.0001120837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009265137,"about_ca_topic_score_gemma":0.0003105761,"domain_scores_codex":[0.9980159,0.0001160356,0.0001949072,0.0005262148,0.0007527428,0.0003941422],"domain_scores_gemma":[0.9976314,0.0008008525,0.00002639193,0.001173231,0.0001530616,0.0002150485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002372026,0.0008492789,0.8578502,0.00001676686,0.0000406593,0.0001550809,0.003720831,0.002994323,0.03687645,0.0005911043,0.003995889,0.0928857],"study_design_scores_gemma":[0.0005190738,0.0006216955,0.7464831,0.000002145827,0.000003900588,0.00002934438,0.00006981703,0.2476618,0.003848633,0.0001961248,0.0003212425,0.0002430566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8960115,0.00001010144,0.1021748,0.0003170002,0.0003301143,0.0002428619,0.000001532134,0.000811771,0.0001002568],"genre_scores_gemma":[0.8416227,5.821354e-7,0.157568,0.00008048972,0.00008315765,0.00002880806,0.000001340103,0.00001440699,0.0006005852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2446675,"threshold_uncertainty_score":0.4503566,"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."}}