{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01237721,0.001042923,0.0006027484,0.003789742,0.0005284668,0.002778204,0.002144839,0.0008931967,0.004585981],"category_scores_gemma":[0.05400953,0.0005206932,0.0006562183,0.001225456,0.00148173,0.003277087,0.001894184,0.0008189821,0.0005624024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001902801,"about_ca_system_score_gemma":0.001353786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001728628,"about_ca_topic_score_gemma":0.001577446,"domain_scores_codex":[0.9907348,0.004083559,0.0006209703,0.0005463772,0.003781443,0.0002327724],"domain_scores_gemma":[0.9448035,0.0340919,0.003893882,0.005721027,0.0110973,0.0003924154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00209925,0.001028626,0.01878053,0.003979078,0.0003513242,0.0005165816,0.007465704,0.2260292,0.1385294,0.09646784,0.002979054,0.5017735],"study_design_scores_gemma":[0.0002626437,0.001257128,0.009262164,0.0005795241,0.0001901687,0.0003471545,0.003727859,0.7509828,0.1736317,0.04424631,0.0153156,0.0001969485],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05825235,0.0002486158,0.9345323,0.0001741501,0.00003988478,0.0002682081,0.000225678,0.002377612,0.003881131],"genre_scores_gemma":[0.5159574,0.0003400693,0.4805937,0.00007198859,0.00001465944,0.0006408421,0.0005603586,0.0005242516,0.001296707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01237721,"threshold_uncertainty_score":0.0654577,"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."}}