{"id":"W2128592203","doi":"10.1016/j.fss.2005.11.009","title":"Bayesian reliability analysis for fuzzy lifetime data","year":2005,"lang":"en","type":"article","venue":"Fuzzy Sets and Systems","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":234,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Weibull distribution; Mathematics; Reliability (semiconductor); Bayesian probability; Membership function; Fuzzy logic; Statistics; Estimation theory; Algorithm; Data mining; Computer science; Fuzzy set; Artificial intelligence","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":[0.0133011,0.0008742319,0.002104643,0.003062814,0.0006345701,0.001998179,0.001783036,0.001783621,0.002675303],"category_scores_gemma":[0.05836606,0.001018212,0.001298405,0.002110265,0.001389564,0.004013445,0.001197306,0.001826807,0.0005608046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001686052,"about_ca_system_score_gemma":0.001002177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004331625,"about_ca_topic_score_gemma":0.003468495,"domain_scores_codex":[0.9959276,0.002017238,0.000200295,0.0005463978,0.001072619,0.0002357591],"domain_scores_gemma":[0.9667941,0.02610394,0.001938399,0.002462986,0.00248177,0.0002186693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000186509,0.00005160801,0.003663205,0.0002318299,0.0002720964,0.0001603745,0.0002529618,0.7562492,0.001107983,0.1624898,0.002484998,0.07284947],"study_design_scores_gemma":[0.00001028939,0.00002405381,0.001239112,0.00003365803,0.00004194455,0.00008746823,0.00002718214,0.8729566,0.0003564596,0.1244362,0.0007613772,0.00002556123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0182694,0.000739765,0.9791215,0.0002935579,0.00002626954,0.00002977646,0.0001368443,0.0001137216,0.001269171],"genre_scores_gemma":[0.8580639,0.00180474,0.1342645,0.0001837103,0.0002900249,0.0002490295,0.0009723948,0.000167148,0.004004587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0133011,"threshold_uncertainty_score":0.07034379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0585888381902399,"score_gpt":0.317873425447097,"score_spread":0.2592845872568571,"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."}}