{"id":"W2088502728","doi":"10.1145/2362336.2362348","title":"Modeling towards incremental early analyzability of networked avionics systems using virtual integration","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Division of Computer and Network Systems; National Science Foundation","keywords":"Avionics; Computer science; Latency (audio); Integrated modular avionics; Shared resource; Software; Embedded system; Architecture; Distributed computing; 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":[0.0014566,0.001230301,0.0005341506,0.001143055,0.0005097069,0.001586026,0.001934576,0.0007844488,0.001917074],"category_scores_gemma":[0.00521478,0.0008496248,0.001268607,0.0005285447,0.001369533,0.002567054,0.001456123,0.002092983,0.0002858916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001494527,"about_ca_system_score_gemma":0.001391618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005358188,"about_ca_topic_score_gemma":0.0031061,"domain_scores_codex":[0.9988972,0.000238572,0.00005951288,0.0001639722,0.0004548877,0.0001858381],"domain_scores_gemma":[0.9978403,0.001220704,0.0002324426,0.0002732131,0.000363388,0.00006993951],"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":[0.00003778985,0.00002864929,0.0005684748,0.00004242692,0.00001697319,0.00007243451,0.0001087618,0.9633077,0.005253358,0.02347709,0.0001309772,0.006955286],"study_design_scores_gemma":[0.000002146624,0.00001154523,0.00004409716,0.00000321259,0.000007560239,0.000007985783,0.000005404956,0.9944106,0.001249969,0.003988893,0.00026593,0.000002727592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03835304,0.000128838,0.9581359,0.00005747879,0.00001535251,0.00005975458,0.00004898497,0.000494047,0.002706558],"genre_scores_gemma":[0.7847595,0.0003325513,0.2108356,0.00006283483,0.00002945217,0.0002332779,0.0001801754,0.0002642543,0.003302336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005358188,"threshold_uncertainty_score":0.01084358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04981730269383431,"score_gpt":0.2894205370019494,"score_spread":0.2396032343081151,"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."}}