{"id":"W4321239522","doi":"10.1002/qre.3287","title":"Robust inference for nondestructive one‐shot device testing under step‐stress model with exponential lifetimes","year":2023,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Educación, Cultura y Deporte; Ministerio de Ciencia, Innovación y Universidades","keywords":"Accelerated life testing; Censoring (clinical trials); Quantile; Estimator; Exponential distribution; Statistics; Robustness (evolution); Inference; Reliability (semiconductor); Statistical inference; Computer science; Statistical hypothesis testing; Stress (linguistics); Exponential function; Reliability engineering; Mathematics; Weibull distribution; Engineering; Power (physics); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003723837,0.0001274555,0.0001607767,0.00005756288,0.0001094071,0.00005919765,0.0001236991,0.00006732301,0.00002692727],"category_scores_gemma":[0.002809422,0.0001191052,0.00003410508,0.0001796308,0.00005775415,0.0001148863,0.00005012698,0.0001238073,0.0000055815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006449296,"about_ca_system_score_gemma":0.00004985238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000221498,"about_ca_topic_score_gemma":0.000005216631,"domain_scores_codex":[0.9989437,0.00002174966,0.0003371067,0.0002763674,0.0002573857,0.0001636579],"domain_scores_gemma":[0.9971686,0.002134526,0.00008941132,0.0001562043,0.0003697838,0.00008148246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002769454,0.00009773309,0.0004707895,0.0001990961,0.00003899662,2.536059e-7,0.0001026379,0.2866261,0.000354306,0.7117332,0.000102068,0.0002471182],"study_design_scores_gemma":[0.0003609383,0.00002057932,0.02406383,0.00007913384,0.00002385896,0.000001387321,0.00009481564,0.9223883,0.0002235387,0.05253581,0.00004400467,0.0001638087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1291921,0.000001720799,0.8685132,0.0009455851,0.00006173294,0.0002514455,0.0006270825,0.0002132852,0.0001938142],"genre_scores_gemma":[0.7501505,0.000002272707,0.2492809,0.00003425183,0.00005070544,0.0001548221,0.000209892,0.00001334508,0.0001032863],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6591974,"threshold_uncertainty_score":0.4856967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.281400668614178,"score_gpt":0.4079010989045551,"score_spread":0.1265004302903772,"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."}}