{"id":"W4253846878","doi":"10.1002/9780470012505.tar021","title":"Reliability Classifications","year":2004,"lang":"en","type":"other","venue":"Encyclopedia of Actuarial Science","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Compounding; Reliability (semiconductor); Convolution (computer science); Closure (psychology); Mixing (physics); Computer science; Reliability engineering; Mathematics; Engineering; Artificial intelligence; Materials science; Economics; Physics; Thermodynamics","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":["metaresearch","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005768747,0.0002874492,0.0006166986,0.0007929077,0.0002440742,0.0001514351,0.003954963,0.0003689121,0.004417585],"category_scores_gemma":[0.0143214,0.0001970271,0.000220352,0.002621153,0.003629707,0.0004779827,0.0004487517,0.0003474997,0.0008343597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001978231,"about_ca_system_score_gemma":0.003194842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001060609,"about_ca_topic_score_gemma":0.0003351561,"domain_scores_codex":[0.9935138,0.0001530591,0.001029846,0.001392325,0.003423168,0.0004877873],"domain_scores_gemma":[0.9951154,0.00071134,0.0009152549,0.002479857,0.000475527,0.0003026067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006609911,0.00089393,0.00105544,0.00006521077,0.00002461273,0.00000534052,0.00260627,0.0007851978,0.0007148911,0.147579,0.7747127,0.07149123],"study_design_scores_gemma":[0.0002093771,0.00005376684,0.002477273,0.00005273726,0.00001615182,0.000001325865,0.00006155523,0.00007269641,0.00007940542,0.1401977,0.8565132,0.0002648138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005840815,0.0001285719,0.006744239,0.0005256711,0.002956818,0.00058752,0.0001094869,0.0001259977,0.9882376],"genre_scores_gemma":[0.09144788,0.0007708147,0.0215717,0.00009452554,0.00125623,0.0000475581,0.0000102878,0.0001639278,0.8846371],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1036005,"threshold_uncertainty_score":0.9999436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05733989151533516,"score_gpt":0.3633109354126243,"score_spread":0.3059710438972891,"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."}}