{"id":"W4408054024","doi":"10.1145/3721125","title":"Unraveling Code Clone Dynamics in Deep Learning Frameworks","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Software Engineering and Methodology","topic":"Software Engineering Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Toronto; Université du Québec à Montréal","funders":"","keywords":"Computer science; Code (set theory); Software engineering; Artificial intelligence; Data science; Programming language","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":[0.004567116,0.0004445414,0.0004339284,0.003020448,0.0006622813,0.001526167,0.001181207,0.0007431563,0.0004457586],"category_scores_gemma":[0.0405027,0.0003634454,0.0004738857,0.001875764,0.001729992,0.003946258,0.001686953,0.001324553,0.0001148043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766308,"about_ca_system_score_gemma":0.001342619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01068982,"about_ca_topic_score_gemma":0.01443378,"domain_scores_codex":[0.9972941,0.0006618699,0.0001653544,0.0006855628,0.0008299243,0.0003630544],"domain_scores_gemma":[0.9718847,0.01417607,0.007049093,0.002782367,0.003256946,0.0008507058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002737075,0.0002517254,0.7791653,0.0002034906,0.0001775225,0.0007121423,0.005145971,0.04488882,0.007687228,0.006488162,0.001471469,0.1535345],"study_design_scores_gemma":[0.0000356514,0.0002799066,0.355971,0.0001218564,0.0001358061,0.0007790343,0.002478149,0.6141773,0.006190819,0.01451562,0.005236694,0.00007812979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872956,0.0005153784,0.01092559,0.0002558964,0.000007378844,0.0000170752,0.00008984713,0.0003140181,0.0005792691],"genre_scores_gemma":[0.993064,0.00009876132,0.006292526,0.00004563258,0.000004399712,0.00001920473,0.0001891602,0.00005847996,0.0002279195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01068982,"threshold_uncertainty_score":0.02415353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03839091002517494,"score_gpt":0.3237694378525945,"score_spread":0.2853785278274196,"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."}}