{"id":"W2925127136","doi":"10.1007/s11219-018-9437-3","title":"Testing self-healing cyber-physical systems under uncertainty: a fragility-oriented approach","year":2019,"lang":"en","type":"article","venue":"Software Quality Journal","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Horizon 2020 Framework Programme; Norges Forskningsråd","keywords":"Fragility; Reliability engineering; Normality; Computer science; Reliability (semiconductor); Cyber-physical system; Data mining; Engineering; Mathematics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003802481,0.0004022081,0.000663919,0.0002317314,0.0005845209,0.0007376798,0.001319511,0.0001910835,0.000004268882],"category_scores_gemma":[0.002277284,0.0003510251,0.0002445272,0.001042716,0.00007362645,0.0006964321,0.0004087612,0.001208559,0.00006055661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004090498,"about_ca_system_score_gemma":0.0004712151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000427374,"about_ca_topic_score_gemma":9.07589e-7,"domain_scores_codex":[0.995387,0.0009014855,0.0008913888,0.0008112765,0.001167248,0.0008416513],"domain_scores_gemma":[0.9942878,0.002727387,0.000639811,0.001177315,0.0007771322,0.0003905093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001438142,0.004180976,0.630176,0.002323812,0.0009155284,0.0002248075,0.02204707,0.1194564,0.0008043359,0.1149248,0.01351378,0.09128857],"study_design_scores_gemma":[0.002353506,0.0008946191,0.03088864,0.001191143,0.00009622679,0.002946803,0.0007637883,0.7796924,0.00007792472,0.1764179,0.002280673,0.002396305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2131119,0.0001736458,0.7741698,0.0001506888,0.0008486091,0.0003105159,0.000005189641,0.010833,0.0003967088],"genre_scores_gemma":[0.5869105,0.00000181538,0.4123117,0.0002931548,0.0003736795,0.00001716336,0.000005159036,0.00003165197,0.00005510158],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.660236,"threshold_uncertainty_score":0.9998942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04131213216160864,"score_gpt":0.308153895772097,"score_spread":0.2668417636104884,"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."}}