{"id":"W4415223970","doi":"10.1016/j.procs.2025.08.219","title":"AI-Driven Agile Systems Engineering Approach for Managing Cross-System Interactions","year":2025,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Anesthesiologists' Society; Ford Motor Company","keywords":"Agile software development; Adaptability; Process (computing); Automotive industry; Requirements engineering; Quality (philosophy); System of systems; Compromise; Product (mathematics)","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000454943,0.0001336854,0.0001371534,0.0005444673,0.0004410924,0.001424766,0.0005112624,0.00002402858,0.000001173086],"category_scores_gemma":[0.00005259245,0.0001295943,0.00003484615,0.001370434,0.00005214299,0.002149496,0.0002808171,0.00007842455,0.00001828266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001099915,"about_ca_system_score_gemma":0.00007693149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001220202,"about_ca_topic_score_gemma":6.052747e-7,"domain_scores_codex":[0.9987963,0.000001793431,0.0002345629,0.0004552901,0.0002059136,0.0003061806],"domain_scores_gemma":[0.9992625,0.00001920549,0.0001006398,0.0001828425,0.0004216734,0.0000131421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003956904,0.0001358278,0.02990038,0.006705072,0.0000684301,0.000002985967,0.000398771,0.4105987,0.00212562,0.5179399,0.01274783,0.01933702],"study_design_scores_gemma":[0.0001960291,0.000001733673,0.001693396,0.0001176767,0.00001119275,0.00000222447,0.00003455286,0.9867031,0.0001285581,0.0000987348,0.01086298,0.0001498333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006894221,0.00003980097,0.9834418,0.0003023814,0.003475313,0.0005880256,6.981872e-7,0.0003990408,0.004858695],"genre_scores_gemma":[0.9754432,6.484869e-7,0.02252297,0.0004275966,0.00111106,0.0001762809,0.00001636069,0.00001224917,0.0002895908],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.968549,"threshold_uncertainty_score":0.9996119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009596620925693189,"score_gpt":0.2298202925483468,"score_spread":0.2202236716226537,"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."}}