{"id":"W2090222336","doi":"10.1145/1985404.1985411","title":"Automated type-3 clone oracle using Levenshtein metric","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Oracle; clone (Java method); Computer science; Construct (python library); Metric (unit); Scalability; Relation (database); Data mining; Programming language; Theoretical computer science; Database; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004432803,0.0007950084,0.001478505,0.004825802,0.0009189095,0.00369763,0.001660115,0.001188509,0.00140484],"category_scores_gemma":[0.02968419,0.000379112,0.0008718316,0.002557507,0.001307739,0.004124298,0.002067611,0.0009529741,0.0007052392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552334,"about_ca_system_score_gemma":0.001392211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002563762,"about_ca_topic_score_gemma":0.001975638,"domain_scores_codex":[0.9903413,0.00163733,0.001357813,0.001269214,0.004850153,0.000544155],"domain_scores_gemma":[0.9703856,0.01153885,0.003766925,0.005399937,0.00819895,0.000709613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007977334,0.0001890029,0.07137206,0.0005514882,0.0001621914,0.0006397607,0.001761544,0.04657465,0.08586232,0.03685898,0.003883682,0.7513466],"study_design_scores_gemma":[0.00004996371,0.0008095587,0.03001886,0.00009406799,0.0001455862,0.002098544,0.0006450005,0.6637676,0.252735,0.03388601,0.01551157,0.0002382876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1189817,0.0004626054,0.8702924,0.0001242927,0.00003173864,0.0001858478,0.000353845,0.007413364,0.002154194],"genre_scores_gemma":[0.6003339,0.0001843021,0.3963495,0.00004791841,0.00002667733,0.0001483585,0.0009617523,0.0004812923,0.001466262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004825802,"threshold_uncertainty_score":0.02344316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0943181722566206,"score_gpt":0.3091308243302671,"score_spread":0.2148126520736465,"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."}}