{"id":"W3022832263","doi":"","title":"Pattern-based transformation of SysML models into fault tree models.","year":2019,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Fault tree analysis; Computer science; Transformation (genetics); Model transformation; Systems Modeling Language; Tree (set theory); Unified Modeling Language; Programming language; Artificial intelligence; Reliability engineering; Mathematics; Engineering; Software","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001580755,0.0006008968,0.0003847993,0.001070353,0.0003607322,0.001783017,0.001541728,0.001105475,0.006894469],"category_scores_gemma":[0.010165,0.0006091084,0.001445222,0.0009054625,0.0006021754,0.002380854,0.001582165,0.001560632,0.002446671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007030941,"about_ca_system_score_gemma":0.001284438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005303359,"about_ca_topic_score_gemma":0.006641855,"domain_scores_codex":[0.9984075,0.0005040358,0.000175593,0.0002014956,0.0006018586,0.0001095578],"domain_scores_gemma":[0.9959359,0.001978055,0.0002911207,0.00101764,0.0007098952,0.00006743698],"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":[0.0007775506,0.0006239172,0.005009418,0.0009950141,0.0003215979,0.001759525,0.001960263,0.2919277,0.03849228,0.1379284,0.04863945,0.4715649],"study_design_scores_gemma":[0.00007865122,0.00009261352,0.0005670465,0.0001034553,0.00007334631,0.0002871742,0.00019849,0.8711902,0.02997403,0.05988349,0.03751715,0.00003431972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008052471,0.00006768174,0.9708723,0.0002687516,0.00008824797,0.0002236088,0.001425737,0.01549731,0.003503797],"genre_scores_gemma":[0.2104069,0.0002509799,0.773022,0.000212258,0.00003355806,0.0004797847,0.007291556,0.002282768,0.006020249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006894469,"threshold_uncertainty_score":0.02306432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06971778443917276,"score_gpt":0.3527116704378132,"score_spread":0.2829938859986404,"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."}}