{"id":"W1989306111","doi":"10.1145/2791060.2791104","title":"Modeling aerospace systems product lines in SysML","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Systems Modeling Language; Avionics; Aerospace; Unified Modeling Language; Systems engineering; Computer science; Software engineering; Modeling language; Software; Product (mathematics); Software product line; Engineering; Manufacturing engineering; Reliability engineering; Software development; Aerospace engineering; Operating system","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":[0.001773384,0.001013733,0.0003623812,0.001067195,0.000521305,0.003079066,0.001378174,0.001043166,0.004605199],"category_scores_gemma":[0.003810083,0.0007596065,0.001109774,0.001024325,0.0007303523,0.00285564,0.0009795164,0.001630052,0.002109888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009850252,"about_ca_system_score_gemma":0.001679524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006593619,"about_ca_topic_score_gemma":0.008352215,"domain_scores_codex":[0.9983053,0.0005542272,0.0002404634,0.0002303391,0.0005837594,0.00008580556],"domain_scores_gemma":[0.9977063,0.001029656,0.0002699356,0.0004844558,0.000454568,0.00005500238],"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":[0.0002158313,0.0001861152,0.003869229,0.001090924,0.0001330477,0.0009944815,0.00262568,0.3474732,0.0181693,0.3831289,0.02394238,0.2181709],"study_design_scores_gemma":[0.00009287944,0.0001208535,0.0005980582,0.0001850937,0.00007987717,0.0003835307,0.0001691827,0.6553922,0.01673646,0.06802563,0.2581624,0.00005390773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004376223,0.0001117265,0.9850194,0.0001922136,0.00003663329,0.0001439295,0.0008050223,0.005966108,0.003348634],"genre_scores_gemma":[0.06759042,0.0005221586,0.9207538,0.0001633809,0.00004358966,0.0004973021,0.003139018,0.001214421,0.006075978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006593619,"threshold_uncertainty_score":0.01540595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1316520874047581,"score_gpt":0.3173314519011728,"score_spread":0.1856793644964148,"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."}}