{"id":"W2005825826","doi":"10.1016/s0378-3758(99)00113-5","title":"Empirical Bayes estimation for truncation parameters","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Bayes' theorem; Truncation (statistics); Estimator; Statistics; Bayes estimator; Prior probability; Mean squared error; Bayes error rate; Empirical distribution function; Applied mathematics; Econometrics; Bayes classifier; Bayesian probability","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":[0.02754248,0.001491041,0.004194334,0.003071936,0.001747673,0.004234305,0.004661716,0.003770524,0.01038295],"category_scores_gemma":[0.1894156,0.002940493,0.002554673,0.002713612,0.004692754,0.01126262,0.004108903,0.008271453,0.002564133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003458848,"about_ca_system_score_gemma":0.005216957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009524559,"about_ca_topic_score_gemma":0.008419452,"domain_scores_codex":[0.989521,0.00679746,0.0006765643,0.001226077,0.001338845,0.0004399385],"domain_scores_gemma":[0.849318,0.1309836,0.003580542,0.01029801,0.004760032,0.001059808],"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":[0.0002291941,0.0000867429,0.002596496,0.0003321592,0.0002278764,0.0001829436,0.0003330149,0.2039174,0.0004228199,0.7152174,0.007122944,0.06933105],"study_design_scores_gemma":[0.0000454776,0.00001576612,0.0003412691,0.0001417481,0.0000456975,0.00006329337,0.00003492799,0.4045219,0.0002497114,0.5927463,0.001764705,0.00002917976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003184598,0.0005548649,0.9942244,0.0004596317,0.0000615344,0.00003539171,0.0001472847,0.0001947005,0.00113761],"genre_scores_gemma":[0.2322951,0.003455945,0.7456837,0.0008518284,0.0005618565,0.0009635108,0.002334267,0.0009152693,0.01293863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02754248,"threshold_uncertainty_score":0.1456603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1605221262907282,"score_gpt":0.463789269440456,"score_spread":0.3032671431497278,"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."}}