{"id":"W3183735209","doi":"10.1002/sys.21592","title":"MBSE delivers significant return on investment in evolutionary development of complex SoS","year":2021,"lang":"en","type":"article","venue":"Systems Engineering","topic":"Systems Engineering Methodologies and Applications","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science; Process (computing); Return on investment; Baseline (sea); Quality (philosophy); Systems engineering; Engineering; Operating system; Production (economics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0002835807,0.0002171629,0.0003572588,0.0001999838,0.00002879654,0.00001494434,0.0001484293,0.0000995943,0.000009457493],"category_scores_gemma":[0.00006375267,0.0002372355,0.00005638948,0.0003967464,0.0000116191,0.00004505638,0.00003607737,0.0001646222,0.00001322201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003473974,"about_ca_system_score_gemma":0.00005296576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001961139,"about_ca_topic_score_gemma":0.000003349273,"domain_scores_codex":[0.9986354,0.00003588883,0.0005883919,0.0002239411,0.0002147962,0.0003015565],"domain_scores_gemma":[0.9993404,0.0001520071,0.00004427816,0.0003390338,0.00005434571,0.00006989669],"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":[0.000001722161,0.00002104605,0.000124033,0.0004789974,0.0000492289,0.00001342177,0.0003200812,0.824383,0.17106,0.003108499,0.0002179876,0.0002220246],"study_design_scores_gemma":[0.0006095432,0.0000286251,0.01271063,0.0009298703,0.00001464114,0.00003014698,0.001139199,0.9193361,0.03539701,0.0000212404,0.02913325,0.0006497349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7556303,0.00266062,0.2358345,0.00002649967,0.001581685,0.0007777752,0.00003497878,0.0008459267,0.002607716],"genre_scores_gemma":[0.9716892,0.00002885318,0.02788071,0.000005849382,0.00007259123,0.0001778934,0.00002938252,0.00004782316,0.00006770185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2160589,"threshold_uncertainty_score":0.9674181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05833198549743977,"score_gpt":0.2407030128020985,"score_spread":0.1823710273046588,"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."}}