{"id":"W4412450541","doi":"10.3390/systems13070584","title":"MBSE 2.0: Toward More Integrated, Comprehensive, and Intelligent MBSE","year":2025,"lang":"en","type":"article","venue":"Systems","topic":"Systems Engineering Methodologies and Applications","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hog Administrative Marketing Services (Canada)","funders":"National Key Research and Development Program of China; Natural Science Foundation of Beijing Municipality; Beihang University; National Natural Science Foundation of China","keywords":"Computer science","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":[0.0001313823,0.000169172,0.0002749419,0.0001145729,0.00004134284,0.00005978315,0.0001382347,0.00009924851,0.000003592807],"category_scores_gemma":[0.00003292431,0.0001498823,0.00004056439,0.0002628494,0.00003386744,0.00003541076,0.00004104382,0.0001388628,0.00002094044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006745395,"about_ca_system_score_gemma":0.00001106745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001269852,"about_ca_topic_score_gemma":0.000002878581,"domain_scores_codex":[0.9992383,0.00003661074,0.0002815923,0.0001788996,0.00007344673,0.000191191],"domain_scores_gemma":[0.9994373,0.0001483826,0.00002116463,0.000290742,0.00005512028,0.00004728164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002865434,0.00007476375,0.002029683,0.008591241,0.001015011,0.00003430323,0.003386894,0.7448531,0.05638171,0.04214541,0.06973656,0.07172268],"study_design_scores_gemma":[0.0003578719,0.00002638679,0.003209444,0.0006748817,0.00004865237,0.00004970555,0.006664243,0.2619514,0.003232256,0.0002143329,0.7230685,0.0005023942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1983457,0.02694877,0.7651387,0.000260857,0.003436306,0.0009412071,0.00003036181,0.001515802,0.003382357],"genre_scores_gemma":[0.996758,0.0004678786,0.001612079,0.00002504,0.00006002887,0.0001770711,0.00001050495,0.000025651,0.0008637186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7984124,"threshold_uncertainty_score":0.6112021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04648730203588256,"score_gpt":0.287843855285314,"score_spread":0.2413565532494315,"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."}}