{"id":"W4402217410","doi":"10.1016/j.cie.2024.110536","title":"Robust inference for an interval-monitored step-stress experiment with competing risks for failure with an application to capacitor data","year":2024,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Ministerio de Universidades; Natural Sciences and Engineering Research Council of Canada","keywords":"Inference; Reliability engineering; Interval (graph theory); Computer science; Stress (linguistics); Engineering; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03364477,0.001119037,0.001917171,0.001551617,0.0004835911,0.001588918,0.003136155,0.002480537,0.001591841],"category_scores_gemma":[0.09563924,0.0007304988,0.002056256,0.001325728,0.003257141,0.002306622,0.002056412,0.002871503,0.0002173421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001165903,"about_ca_system_score_gemma":0.001221932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00220994,"about_ca_topic_score_gemma":0.001166405,"domain_scores_codex":[0.9894539,0.00686147,0.0003731721,0.001799,0.001205379,0.0003070429],"domain_scores_gemma":[0.8445402,0.1404291,0.005508727,0.006632931,0.002298564,0.0005904053],"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":[0.000820831,0.0002363534,0.01370662,0.0004899328,0.0009381737,0.0004719018,0.0003413736,0.7082691,0.006758124,0.188322,0.0008066219,0.07883891],"study_design_scores_gemma":[0.00004490628,0.0001646005,0.00200529,0.00002261437,0.00006489443,0.00007915487,0.00002179663,0.9508693,0.001253859,0.0450022,0.0004341789,0.00003714835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01966906,0.0001695356,0.9795814,0.00008425308,0.00001307351,0.00005643079,0.00009836216,0.0001397276,0.0001881798],"genre_scores_gemma":[0.5920691,0.0004837532,0.404293,0.0001911891,0.00008664648,0.000498497,0.0007136684,0.00009008141,0.001573982],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03364477,"threshold_uncertainty_score":0.1779327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2726649838724733,"score_gpt":0.3712985966494697,"score_spread":0.09863361277699634,"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."}}