{"id":"W2086340664","doi":"10.5555/2755753.2757191","title":"Towards an accurate reliability, availability and maintainability analysis approach for satellite systems based on probabilistic model checking","year":2015,"lang":"en","type":"article","venue":"Design, Automation, and Test in Europe","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Concordia University","funders":"","keywords":"Maintainability; Computer science; Markov chain; Erlang distribution; Avionics; Reliability engineering; Probabilistic logic; Geostationary orbit; Model checking; Reliability (semiconductor); Satellite system; Exponential distribution; Real-time computing; Satellite; Markov model; Geostationary Operational Environmental Satellite; Algorithm; Global Positioning System; GNSS applications; Engineering; Telecommunications; Aerospace engineering; Statistics","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009508323,0.0003041752,0.0005790611,0.0004696205,0.0002207897,0.0006601114,0.0006146721,0.0001315241,0.000001602368],"category_scores_gemma":[0.01007307,0.0002585409,0.00009033774,0.002593793,0.0002520336,0.0007622109,0.0001569211,0.0002080036,0.000001574399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002559914,"about_ca_system_score_gemma":0.0005451654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001833952,"about_ca_topic_score_gemma":0.00001765179,"domain_scores_codex":[0.995643,0.001238064,0.0007592071,0.001296146,0.0006039947,0.0004595968],"domain_scores_gemma":[0.9949901,0.001944709,0.0001813169,0.001260857,0.001271272,0.0003517364],"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":[0.00006369017,0.0008659528,0.09317772,0.000490054,0.00003590683,0.000002617728,0.001046044,0.8942063,0.00001806881,0.004676106,0.00001734188,0.005400233],"study_design_scores_gemma":[0.0004960543,0.0003329903,0.05902373,0.00001826959,0.00006891048,0.000002006774,0.00005295889,0.9326553,0.00002417347,0.007017304,0.00004331708,0.0002649634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1033815,0.0001058568,0.8943848,0.0002290753,0.00002722997,0.00139738,0.00001736352,0.0002342839,0.0002224834],"genre_scores_gemma":[0.8873451,0.00002182228,0.112249,0.00005846313,0.00002043485,0.000208347,0.0000546142,0.00001567686,0.0000265302],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7839636,"threshold_uncertainty_score":0.9999867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07319186676392403,"score_gpt":0.3070104834331236,"score_spread":0.2338186166691996,"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."}}