{"id":"W3151855275","doi":"10.1109/iwsc.2012.6227876","title":"Towards qualitative comparison of Simulink model clone detection approaches","year":2012,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Adaptability; clone (Java method); Computer science; Relevance (law); Visualization; Plan (archaeology); Software engineering; Machine learning; Data mining; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007298738,0.00008419559,0.0001543631,0.0001082185,0.00003300564,0.00002196785,0.0003842629,0.00005497019,0.00000457369],"category_scores_gemma":[0.0003559743,0.00007374443,0.00004215563,0.0003302153,0.00003591645,0.0004175268,0.0001716887,0.0001393292,0.00002144559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004704463,"about_ca_system_score_gemma":0.00003057532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003838805,"about_ca_topic_score_gemma":0.000001857818,"domain_scores_codex":[0.9989651,0.00007294968,0.0001867813,0.0001543722,0.0003551013,0.000265625],"domain_scores_gemma":[0.9989946,0.0004735975,0.00004193316,0.0003191432,0.00007301051,0.00009772546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003378885,0.000956416,0.00766177,0.0002245277,0.0001205986,4.936275e-7,0.1793484,0.3454187,0.009135136,0.1112272,0.000468168,0.3454048],"study_design_scores_gemma":[0.00009886357,0.00004659454,0.001360415,0.000003340179,0.000001822335,5.975194e-7,0.0004907363,0.9361564,0.06108978,0.0006415539,0.00002247079,0.00008745379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1315159,0.0001259692,0.8672859,0.00007017281,0.0000956964,0.0000842334,6.35053e-7,0.000180008,0.0006414885],"genre_scores_gemma":[0.8132722,8.116103e-7,0.1865878,0.00000648739,0.00002719467,0.00001081444,5.506177e-7,0.000005979629,0.00008817353],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6817563,"threshold_uncertainty_score":0.300721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2096295790966588,"score_gpt":0.3958619410182621,"score_spread":0.1862323619216033,"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."}}