{"id":"W2784276292","doi":"10.6000/1929-6029.2017.06.04.4","title":"Lindley Approximation Technique for the Parameters of Lomax Distribution","year":2017,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lomax distribution; Prior probability; Applied mathematics; Mathematics; Exponential function; Bayesian probability; Bayes' theorem; Exponential distribution; Bayes estimator; Statistics; Mathematical optimization; Maximum likelihood; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00581029,0.00007495977,0.0001975903,0.0001319617,0.0002082729,0.00009912394,0.001223551,0.0001036814,0.0001612027],"category_scores_gemma":[0.08565528,0.00005343606,0.00006744738,0.00009948701,0.0006850383,0.0001067946,0.0001173095,0.0005345714,0.000003468886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001758319,"about_ca_system_score_gemma":0.0003345209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004422102,"about_ca_topic_score_gemma":0.00002450281,"domain_scores_codex":[0.9966329,0.0001440018,0.0008473273,0.0001097162,0.002081211,0.0001848967],"domain_scores_gemma":[0.9866534,0.009635384,0.0006179391,0.0002630816,0.002713583,0.000116598],"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":[0.0001230916,0.0002464069,0.000201748,0.00004958776,0.00005164563,0.00001554717,0.00006493847,0.00001332079,0.0001558476,0.9381478,0.009223013,0.05170703],"study_design_scores_gemma":[0.001213491,0.0001429033,0.009802409,0.0003585635,0.00002367266,0.00004661331,0.0001783267,0.0363126,0.002683925,0.9466337,0.002520481,0.00008329353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001616735,0.00001934438,0.9910218,0.005421651,0.0002322433,0.0004269401,0.001037008,0.000003117979,0.0002211651],"genre_scores_gemma":[0.8742508,0.0001521134,0.1251802,0.00003031844,0.0001321742,0.0001200905,0.00008420902,0.000009512844,0.00004057012],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8726341,"threshold_uncertainty_score":0.9220467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2275078714619187,"score_gpt":0.551320226571386,"score_spread":0.3238123551094673,"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."}}