{"id":"W1998569777","doi":"10.1109/icsme.2014.55","title":"Recommending Clones for Refactoring Using Design, Context, and History","year":2014,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Code refactoring; Computer science; clone (Java method); Cloning (programming); Context (archaeology); Software engineering; Software maintenance; Source code; Programming language; Code (set theory); Software development; Software","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":[0.002170528,0.001429626,0.0009929693,0.00594232,0.0006379635,0.001384046,0.001211228,0.001416704,0.0006640865],"category_scores_gemma":[0.01486604,0.0004922295,0.001102113,0.002439682,0.0003275737,0.001949692,0.0006802891,0.0009258179,0.0007664794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008426423,"about_ca_system_score_gemma":0.001403122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009541457,"about_ca_topic_score_gemma":0.02129504,"domain_scores_codex":[0.9980448,0.00033587,0.0001878386,0.0006731465,0.0006290248,0.00012921],"domain_scores_gemma":[0.9878495,0.005773686,0.001499155,0.001255365,0.003154851,0.0004673407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003390935,0.0004730389,0.3103689,0.0005918738,0.0002572844,0.0005728086,0.0007952332,0.03175646,0.0210956,0.0008150254,0.01120284,0.6217319],"study_design_scores_gemma":[0.00008040595,0.0005149174,0.08712965,0.000229064,0.0005024965,0.001047805,0.0005604564,0.8679717,0.02393043,0.003369709,0.01455406,0.0001092691],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6792535,0.003367442,0.2990671,0.0007315899,0.0001398559,0.0003756959,0.00369601,0.0104345,0.002934274],"genre_scores_gemma":[0.7377197,0.0006467705,0.2511504,0.000163232,0.00004939748,0.0001788309,0.007976691,0.0004018563,0.001713117],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009541457,"threshold_uncertainty_score":0.0189718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236162076083696,"score_gpt":0.3043010980501205,"score_spread":0.1806848904417508,"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."}}