{"id":"W2171172898","doi":"10.1145/1985404.1985407","title":"Extracting code clones for refactoring using combinations of clone metrics","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Victoria","keywords":"Code refactoring; clone (Java method); Computer science; Code (set theory); Programming language; Cloning (programming); Computational biology; Biology; Genetics; Software; DNA","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004611449,0.0000671155,0.0001104322,0.0002902198,0.0000737372,0.00003110185,0.0004656874,0.00003844589,0.000007066637],"category_scores_gemma":[0.001438389,0.00006606419,0.00004322573,0.0007036827,0.00001644584,0.0003755749,0.000144107,0.00008287623,0.000001887584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004841193,"about_ca_system_score_gemma":0.00004382769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009771681,"about_ca_topic_score_gemma":0.000002287245,"domain_scores_codex":[0.999191,0.00001402516,0.0001866301,0.0001735705,0.0002218919,0.00021282],"domain_scores_gemma":[0.9981532,0.00118412,0.00006242385,0.0003134053,0.0002329323,0.0000539701],"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":[0.000029053,0.001594125,0.156189,0.0005213925,0.0002312466,0.00002225464,0.008861159,0.002740862,0.08558897,0.6657329,0.0003425128,0.07814648],"study_design_scores_gemma":[0.001398664,0.0002641122,0.05205328,0.00008094583,0.00002208637,0.00002526511,0.0002096127,0.5916239,0.347845,0.005243015,0.0007229841,0.0005110823],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1665249,0.00004949675,0.8326241,0.00001387337,0.0002519916,0.0001138196,0.00000158914,0.0001462621,0.0002739342],"genre_scores_gemma":[0.6256387,0.000002663007,0.374274,0.000002616434,0.00001161134,0.0000051464,3.004992e-7,0.000006721681,0.00005821326],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6604899,"threshold_uncertainty_score":0.2694019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2161381383002295,"score_gpt":0.3510390307316339,"score_spread":0.1349008924314044,"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."}}