{"id":"W3086435442","doi":"10.1145/3387904.3389262","title":"Investigating Near-Miss Micro-Clones in Evolving Software","year":2020,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"clone (Java method); Commit; Computer science; Software; Code (set theory); Programming language; Source code; Base (topology); Software maintenance; Software system; Biology; Genetics; Mathematics; Database; Set (abstract data type)","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":[0.001920463,0.00026689,0.0003835034,0.002822391,0.0005212061,0.001071179,0.0005794148,0.0006401486,0.0003610496],"category_scores_gemma":[0.0297297,0.0002503323,0.0002698568,0.001934194,0.0005681201,0.002163059,0.0009296622,0.0005160811,0.0001239896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004300525,"about_ca_system_score_gemma":0.0004735412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002305989,"about_ca_topic_score_gemma":0.004221996,"domain_scores_codex":[0.9964892,0.0007339829,0.0002855191,0.0009433628,0.001371716,0.000176271],"domain_scores_gemma":[0.9606131,0.0179035,0.01329416,0.002578801,0.004867235,0.0007431928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001854044,0.0001034512,0.8539032,0.0002249786,0.0001249113,0.0009708336,0.005773556,0.004404483,0.0151225,0.001214832,0.0003340902,0.1176378],"study_design_scores_gemma":[0.00001197259,0.0004186918,0.9200501,0.00007443604,0.0001659351,0.003064265,0.004111282,0.05578017,0.0110765,0.002463693,0.002727795,0.00005516376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889313,0.0003934319,0.01010869,0.00004266925,0.000006108402,0.00002815369,0.00005201966,0.00008702453,0.0003506237],"genre_scores_gemma":[0.9917313,0.0001542144,0.007585192,0.00002218751,0.000007784577,0.0000204748,0.0001465538,0.00002288833,0.0003093852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002822391,"threshold_uncertainty_score":0.01015651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920635138818374,"score_gpt":0.2586888585699809,"score_spread":0.2294825071817971,"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."}}