{"id":"W4381744613","doi":"10.4050/f-0079-2023-18175","title":"Reliability Prediction with No Observed Field Failure but with Known Design Lives","year":2023,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Mean time between failures; Reliability (semiconductor); Reliability engineering; Component (thermodynamics); Failure rate; Hazard; Field (mathematics); Exponential distribution; Reliability theory; Computer science; Function (biology); Engineering; Statistics; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001924833,0.0001381308,0.0001300394,0.00004496542,0.00006003979,0.00004010552,0.00008332263,0.00008208559,0.0001318864],"category_scores_gemma":[0.0001201171,0.00009324188,0.00002500674,0.0003461017,0.00003559131,0.0003125231,0.00001381754,0.0001369812,0.00009856739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004408408,"about_ca_system_score_gemma":0.00002446172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004665499,"about_ca_topic_score_gemma":0.00006441197,"domain_scores_codex":[0.9992456,0.00002817749,0.0001487968,0.0002184744,0.0001385137,0.0002204377],"domain_scores_gemma":[0.9993536,0.0001540948,0.00001756926,0.0002916402,0.0001343483,0.00004871732],"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":[0.0001100171,0.00001906873,0.001678481,0.0001153837,0.00002554375,0.000004188538,0.0001846302,0.9794611,0.0008665657,0.00006215709,0.01706894,0.0004038955],"study_design_scores_gemma":[0.000655206,0.0008299589,0.008371481,0.000134575,0.00003212855,0.0000073601,0.0004401498,0.9772142,0.007695086,0.0002170711,0.004088024,0.0003147862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1646117,0.00001755529,0.8205913,0.0006123302,0.0002560143,0.0008227619,0.00001026314,0.002939901,0.01013817],"genre_scores_gemma":[0.9323701,0.0001376145,0.06361774,0.0000713457,0.00009110807,0.0001316672,0.00003992794,0.00004373293,0.003496805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7677584,"threshold_uncertainty_score":0.3802294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342259728374709,"score_gpt":0.1785024111292797,"score_spread":0.1650798138455326,"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."}}