{"id":"W4283204998","doi":"10.1109/ms.2022.3164872","title":"Software Design Trends Supporting Multiconcern Assurance","year":2022,"lang":"en","type":"article","venue":"IEEE Software","topic":"Safety Systems Engineering in Autonomy","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Dependability; Software security assurance; Computer science; Life-critical system; Computer security; Risk analysis (engineering); Variety (cybernetics); Software; Avionics software; Systems engineering; Engineering; Software development; Software quality; Software engineering; Business; Information security; Security service","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":[0.0003922639,0.0003256175,0.0003481621,0.0002171711,0.0003964595,0.00003324882,0.0004863946,0.00008264158,0.0005541588],"category_scores_gemma":[0.0001466613,0.0004025817,0.0001439641,0.0005127524,0.00002696984,0.0001658033,0.0001071799,0.0004735407,0.00008086814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004435251,"about_ca_system_score_gemma":0.00006093864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002124907,"about_ca_topic_score_gemma":0.000003136253,"domain_scores_codex":[0.9980561,0.0000757095,0.0004899161,0.0003574638,0.0003930454,0.0006277459],"domain_scores_gemma":[0.998827,0.0003782901,0.00008718516,0.0005374694,0.00003850362,0.0001315635],"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":[0.000005634513,0.00001440475,0.002696958,0.0001044935,0.00006556702,0.00005777921,0.0008603113,0.9612984,0.0005552376,0.000005254902,0.007537605,0.02679836],"study_design_scores_gemma":[0.00348048,0.000328299,0.01761951,0.0002672399,0.0001537536,0.0006004393,0.0005712697,0.5318446,0.01239317,0.0001843962,0.4284522,0.004104584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02308705,0.0009863077,0.9637449,0.00004616144,0.00492079,0.000353678,0.0001429888,0.006328828,0.0003892454],"genre_scores_gemma":[0.9424925,0.000005648099,0.05548408,0.00005949646,0.0002523079,0.0004183879,0.00003452538,0.0002017347,0.001051315],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9194055,"threshold_uncertainty_score":0.9998426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851287341228297,"score_gpt":0.2295514612861271,"score_spread":0.2110385878738441,"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."}}