{"id":"W4416884873","doi":"10.37665/srjyovr63054","title":"Improving Product Reliability Using Accelerated Stress Testing","year":2012,"lang":"","type":"article","venue":"Soldering and Reliability Conferences","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sciex (Canada); Spinal Cord Injury BC; North Toronto Eye Care","funders":"","keywords":"Reliability (semiconductor); Accelerated life testing; Failure rate; Field (mathematics); Component (thermodynamics); Stress (linguistics); Stress testing (software); Failure mode and effects analysis","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":[0.002928351,0.0009466519,0.00103823,0.0001902913,0.0008950658,0.0005994996,0.0004263279,0.0005413619,0.0001253349],"category_scores_gemma":[0.003948339,0.0008868139,0.0001790398,0.0008869335,0.0008778629,0.001924006,0.0004124309,0.001132837,0.00001260358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003906965,"about_ca_system_score_gemma":0.0004849108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003099545,"about_ca_topic_score_gemma":0.00002943142,"domain_scores_codex":[0.9943318,0.0004089368,0.001498248,0.00138975,0.0005240163,0.001847187],"domain_scores_gemma":[0.9962633,0.0006526716,0.0004137977,0.001161107,0.000867506,0.0006416088],"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":[0.00008772511,0.0007615655,0.4798833,0.008303597,0.000128531,0.000002767981,0.004726307,0.4398391,0.01683579,0.0004241747,0.00003052611,0.04897663],"study_design_scores_gemma":[0.0008027675,0.000208642,0.05084804,0.001396881,0.000339029,0.00003591378,0.002407098,0.926729,0.01446457,0.0006227247,0.0003603449,0.001784973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965653,0.00300723,0.02392938,0.0002206877,0.003290743,0.001403544,0.0000644691,0.0006016412,0.001829312],"genre_scores_gemma":[0.9694335,0.0007308315,0.02879522,0.00002029318,0.0007697314,0.00004608891,0.00002322775,0.00009180738,0.00008923216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4868899,"threshold_uncertainty_score":0.9993582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04721270029100482,"score_gpt":0.2555830456657017,"score_spread":0.2083703453746968,"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."}}