{"id":"W2767601065","doi":"10.1109/icsme.2017.21","title":"SimPact: Impact Analysis for Simulink Models","year":2017,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Computer science; Process (computing); Set (abstract data type); Reliability engineering; Model-based testing; Software engineering; Test case; Machine learning; Engineering; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003616179,0.0001167922,0.0002013014,0.0001511061,0.0004031532,0.0006672248,0.001441598,0.00005287752,0.000009227217],"category_scores_gemma":[0.0005322748,0.00008615167,0.0002809036,0.0001642978,0.00003057141,0.0007172724,0.0002239051,0.00005156342,0.00000743312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002970983,"about_ca_system_score_gemma":0.00004587668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003917694,"about_ca_topic_score_gemma":0.00001183103,"domain_scores_codex":[0.9991671,0.00001093958,0.0001314569,0.0002951675,0.0001359257,0.0002594153],"domain_scores_gemma":[0.9976948,0.0003252196,0.0001239412,0.001630576,0.0001166868,0.0001087823],"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":[0.00004889731,0.0003602732,0.2401596,0.00004442242,0.00208228,0.00003146295,0.001493185,0.1630185,0.0001207755,0.08939412,0.1440756,0.3591709],"study_design_scores_gemma":[0.00008552447,0.00005588266,0.005743741,0.000003378903,0.00003430999,0.000001017358,3.061461e-7,0.7858643,0.0001371795,0.2079073,0.00005804414,0.0001089625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004045938,0.00001541305,0.9870587,0.0004769417,0.0000475128,0.0001114304,0.000004639448,0.005531912,0.002707518],"genre_scores_gemma":[0.678174,0.000001230908,0.3214606,0.0001250982,0.00002739802,0.00000953587,0.000001491261,0.000004790905,0.000195806],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6741281,"threshold_uncertainty_score":0.6434064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08757853160803547,"score_gpt":0.3779971156984662,"score_spread":0.2904185840904307,"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."}}