{"id":"W1984352904","doi":"10.1016/j.csda.2003.11.018","title":"Improved interval estimation for the two-parameter Birnbaum–Saunders distribution","year":2004,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Mathematics; Statistics; Confidence interval; Interval estimation; Applied mathematics; Monte Carlo method; Interval (graph theory); Coverage probability; Sample size determination; Estimation theory; Maximum likelihood; Combinatorics","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":[0.0005578601,0.0002234707,0.0003251777,0.00010571,0.0005739821,0.0002384463,0.0005584491,0.00005769489,0.0001639753],"category_scores_gemma":[0.003504582,0.0001841351,0.0001471545,0.0009237498,0.0002267508,0.0002249801,0.00015286,0.0001451903,0.00004133584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002123207,"about_ca_system_score_gemma":0.000144793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002010285,"about_ca_topic_score_gemma":0.0002303957,"domain_scores_codex":[0.997992,0.00006417139,0.0007144187,0.0005242866,0.0004288406,0.0002762153],"domain_scores_gemma":[0.9935336,0.004675707,0.00034804,0.000790272,0.0005296775,0.0001226662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002260454,0.0001522335,0.00003397403,0.00002813205,0.0007152708,5.514373e-7,0.00003882818,0.1457123,0.000003780474,0.8360922,0.008246165,0.008954005],"study_design_scores_gemma":[0.0005015767,0.00001687164,0.002572769,0.000004984017,0.001395902,0.000001657558,0.00001984568,0.5722496,0.000005495281,0.4227304,0.0003750556,0.0001258591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003314677,0.00001759417,0.9470617,0.001635563,0.00007969952,0.000580511,0.05018233,0.00009663626,0.00001456946],"genre_scores_gemma":[0.4031921,0.000004073813,0.5298693,0.0001519638,0.0000412462,0.000118657,0.06658114,0.00001465603,0.00002693464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4265373,"threshold_uncertainty_score":0.7508813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1076932515340328,"score_gpt":0.412918148381323,"score_spread":0.3052248968472903,"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."}}