{"id":"W2182913975","doi":"","title":"LEVENSHTEIN EDIT DISTANCE-BASED TYPE III CLONE DETECTION USING METRIC TREES","year":2011,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Software Engineering Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Levenshtein distance; Metric (unit); clone (Java method); Computer science; Edit distance; Code (set theory); Mathematics; Artificial intelligence; Algorithm; Biology; Engineering; Programming language; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001414128,0.0007006928,0.0008280578,0.003392127,0.000569505,0.001451949,0.00155253,0.001012811,0.001334165],"category_scores_gemma":[0.009022518,0.0002635417,0.0007323191,0.00267243,0.0006681022,0.001778699,0.001345865,0.0008265332,0.0009154634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000733323,"about_ca_system_score_gemma":0.0008247603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002162982,"about_ca_topic_score_gemma":0.002176075,"domain_scores_codex":[0.9965461,0.0005790434,0.0002964973,0.0005747732,0.001834398,0.0001692324],"domain_scores_gemma":[0.9922172,0.002451747,0.001011354,0.001387732,0.002676418,0.0002555073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000375612,0.0001760837,0.01350883,0.0004105068,0.000215632,0.0003482174,0.0005581469,0.0250916,0.1114662,0.009611038,0.003169505,0.8350686],"study_design_scores_gemma":[0.00003776482,0.0005864901,0.01142451,0.00004728132,0.000101826,0.002300654,0.0001943565,0.7453998,0.2140942,0.01440092,0.01129848,0.0001137184],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06663955,0.000391687,0.9281636,0.00007852438,0.00004844913,0.00007891461,0.0001840505,0.003209948,0.001205331],"genre_scores_gemma":[0.3730257,0.0001670127,0.6234148,0.00006551824,0.00003916214,0.0000817235,0.0007798181,0.0003169649,0.002109207],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003392127,"threshold_uncertainty_score":0.007478774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02734475168536953,"score_gpt":0.2442438465331062,"score_spread":0.2168990948477366,"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."}}