{"id":"W4399169289","doi":"10.1109/ispce61193.2024.10541215","title":"Determining safety critical components - Breaking the mystique!","year":2024,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Component (thermodynamics); Certification; Functional safety; Computer science; Life-critical system; Reliability engineering; Selection (genetic algorithm); Risk analysis (engineering); System safety; Compliance (psychology); Engineering; Business; Software; Psychology; Artificial intelligence; Programming language","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":[0.03902086,0.001782533,0.002346019,0.003893757,0.002507157,0.009905427,0.003436168,0.00588615,0.005806951],"category_scores_gemma":[0.07256973,0.001124048,0.001133554,0.001835492,0.01621247,0.03120223,0.004972653,0.01311627,0.003980996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002704653,"about_ca_system_score_gemma":0.008132532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004091159,"about_ca_topic_score_gemma":0.004954293,"domain_scores_codex":[0.977744,0.007808182,0.001348041,0.0018344,0.01054119,0.0007240475],"domain_scores_gemma":[0.9380193,0.03660654,0.003098012,0.006799001,0.01423053,0.001246649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001634895,0.0002669537,0.005717065,0.003023041,0.0002596347,0.0002930138,0.00211786,0.009766553,0.007982381,0.4495224,0.04376062,0.4771269],"study_design_scores_gemma":[0.00004932795,0.0002579743,0.001798381,0.002192872,0.0001066753,0.000531301,0.003553977,0.009338139,0.006393494,0.7962385,0.1793429,0.0001964002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02030215,0.06102233,0.6882616,0.1982609,0.003689976,0.000296033,0.0002635679,0.001470298,0.02643319],"genre_scores_gemma":[0.2779872,0.05303393,0.6273813,0.02456733,0.003062587,0.0004122714,0.0004198705,0.001384723,0.01175094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03902086,"threshold_uncertainty_score":0.2063645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1557050110887507,"score_gpt":0.4540411778242552,"score_spread":0.2983361667355044,"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."}}