{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004154373,0.0008515672,0.0007798271,0.005744402,0.00114603,0.00366022,0.001667542,0.001126099,0.01593132],"category_scores_gemma":[0.02692681,0.0002881728,0.0008412573,0.003034922,0.00148054,0.00351573,0.001605748,0.001445437,0.004888446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719752,"about_ca_system_score_gemma":0.0009463378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00297734,"about_ca_topic_score_gemma":0.001015999,"domain_scores_codex":[0.993955,0.001150598,0.0005114087,0.0009522598,0.002797564,0.0006333262],"domain_scores_gemma":[0.9753018,0.007291886,0.002923265,0.003912196,0.009926351,0.000644482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001553836,0.00005490403,0.01035959,0.0003408352,0.00004538427,0.0002315961,0.0007985995,0.01872269,0.001649882,0.7799926,0.03909374,0.1485549],"study_design_scores_gemma":[0.00002570052,0.00009961801,0.01083988,0.000617596,0.00004754117,0.0009718984,0.0007584898,0.1116375,0.002602992,0.7357895,0.1365125,0.00009672275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1468459,0.004227592,0.5307643,0.003670323,0.001064598,0.0004974069,0.01093932,0.002816241,0.2991745],"genre_scores_gemma":[0.8766055,0.001841315,0.07371311,0.0005548263,0.0007560754,0.0005376064,0.007553244,0.0005545306,0.03788383],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01593132,"threshold_uncertainty_score":0.05329555,"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."}}