{"id":"W7125699572","doi":"10.5281/zenodo.18377650","title":"Cyber-Physical Co-Design Reliability Framework for ASIL-D Automotive Sensor ECUs with Integrated Hardware–Software Fault Tolerance and Security","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Safety Systems Engineering in Autonomy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dawson College","funders":"","keywords":"Functional safety; Redundancy (engineering); Fault tolerance; Modular design; Reliability (semiconductor); Automotive industry; Fault injection; Electronic control unit; Pipeline (software)","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":[0.0004142984,0.0002533531,0.0002987822,0.0001538583,0.0006046052,0.0003274042,0.00043765,0.0001245167,0.0001932628],"category_scores_gemma":[0.001257211,0.0002485536,0.00005034186,0.0005512906,0.0001447986,0.0001849387,0.0001617106,0.0004645487,0.0002594741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003166057,"about_ca_system_score_gemma":0.000009238844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007951634,"about_ca_topic_score_gemma":1.138197e-7,"domain_scores_codex":[0.99852,0.0001742555,0.0002567829,0.0004609354,0.0002096542,0.0003784288],"domain_scores_gemma":[0.9985098,0.000234827,0.00004866519,0.0004754902,0.0005995685,0.0001316383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001214043,0.000716349,0.0001475999,0.004766822,0.001132876,0.00006537652,0.01705807,0.671685,0.004691683,0.02702898,0.189204,0.08228915],"study_design_scores_gemma":[0.001236549,0.0003767401,0.001403773,0.0005590905,0.00005485893,0.00004990542,0.0004732015,0.2003577,0.004771116,0.001423568,0.7886855,0.0006079871],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02604961,0.00009586158,0.9597384,0.0002365393,0.0001819321,0.001485757,0.0004820648,0.003726829,0.008003027],"genre_scores_gemma":[0.9731223,0.00002186142,0.02490798,0.00005406397,0.0001178081,0.000001439485,0.0003867442,0.001145221,0.0002425654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9470727,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310930228406174,"score_gpt":0.2334396121162419,"score_spread":0.2203303098321801,"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."}}