{"id":"W1989130222","doi":"10.1109/wcre.2007.15","title":"Clone Detection via Structural Abstraction","year":2007,"lang":"en","type":"article","venue":"Proceedings - Working Conference on Reverse Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Abstraction; Programming language; Computer science; Compiler; Cloning (programming); clone (Java method); Syntax; Representation (politics); Intermediate language; Code (set theory); Theoretical computer science; Abstract syntax tree; Code generation; Line (geometry); Algorithm; Artificial intelligence; Parsing; Mathematics; Operating system; Biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006936364,0.0002887682,0.0002024113,0.0005100538,0.000153417,0.0003260191,0.0006145533,0.0001565832,0.00001617931],"category_scores_gemma":[0.00030314,0.0003126945,0.00007201943,0.0008998132,0.00002179254,0.0006319904,0.0001357836,0.0007255538,0.00006219829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002987118,"about_ca_system_score_gemma":0.0000265051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002207345,"about_ca_topic_score_gemma":0.00000212241,"domain_scores_codex":[0.9978643,0.000003646706,0.0003079335,0.0005530739,0.0005732787,0.0006977649],"domain_scores_gemma":[0.9990574,0.0002070293,0.0001012073,0.0002432488,0.0001821553,0.0002089317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001226343,0.00008293217,0.01529103,0.0003730491,0.0001545304,0.000148418,0.002080765,0.009181779,0.554019,0.04037028,0.0001831861,0.3779924],"study_design_scores_gemma":[0.001025898,0.0003499553,0.1456656,0.0007391002,0.00002405616,0.0003472165,0.0001534036,0.7005761,0.1418946,0.0009127151,0.006574987,0.001736355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3802826,0.0000278157,0.6159376,0.00009367928,0.001480801,0.0002052448,2.194007e-7,0.001254773,0.0007172545],"genre_scores_gemma":[0.9810838,0.0000103438,0.01844559,0.00003212103,0.0002874612,0.00001619646,9.461702e-7,0.00003532098,0.00008827758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6913943,"threshold_uncertainty_score":0.9999325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02281679062459205,"score_gpt":0.2538246328404317,"score_spread":0.2310078422158396,"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."}}