{"id":"W2001572404","doi":"10.1016/j.csda.2007.09.021","title":"On the hazard function of Birnbaum–Saunders distribution and associated inference","year":2007,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":141,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Hazard; Monte Carlo method; Statistics; Mathematics; Function (biology); Inference; Applied mathematics; Statistical inference; Survival function; Cumulative distribution function; Econometrics; Computer science; Probability density function; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009523261,0.0001292099,0.0002325996,0.0001061045,0.0002587568,0.00005530257,0.0002139238,0.00005454936,0.0002611646],"category_scores_gemma":[0.005280836,0.0001051452,0.00004407036,0.001017466,0.0002174035,0.0000790726,0.00009346133,0.0001272484,0.00001680075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006725646,"about_ca_system_score_gemma":0.00005152843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004603688,"about_ca_topic_score_gemma":0.0001768728,"domain_scores_codex":[0.9984288,0.0000947707,0.000531011,0.0002933556,0.0004927248,0.0001593963],"domain_scores_gemma":[0.9911547,0.007575182,0.0003440907,0.0004105268,0.000432424,0.00008305806],"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":[0.00001847028,0.0001342275,0.001292924,0.00001209987,0.0004175203,5.850143e-7,0.00001980676,0.001859844,0.000003556999,0.9827814,0.01103471,0.002424858],"study_design_scores_gemma":[0.0001324125,0.0000226686,0.2143149,0.000007218493,0.0006682923,2.310368e-7,0.00002580874,0.2869373,0.000003423161,0.4977039,0.0001048603,0.00007897986],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01269474,0.000006984816,0.9651434,0.0003307312,0.00002382329,0.0001463459,0.02149773,0.00003543769,0.0001208029],"genre_scores_gemma":[0.9424853,0.000006072144,0.02864971,0.0001137649,0.00001054937,0.000006747265,0.02869514,0.000006940072,0.00002577712],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9364937,"threshold_uncertainty_score":0.6322036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1075427135555125,"score_gpt":0.3887252636804368,"score_spread":0.2811825501249243,"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."}}