{"id":"W4254482864","doi":"10.1016/s0169-7161(09)00230-2","title":"Empirical Likelihood Methods","year":2009,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022157,0.002283908,0.003050404,0.003023477,0.0007950406,0.003835754,0.003296949,0.002554933,0.05389863],"category_scores_gemma":[0.008895731,0.001546717,0.001304614,0.004724769,0.001680103,0.003787411,0.001902481,0.00530512,0.04406283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001195588,"about_ca_system_score_gemma":0.001809588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002197367,"about_ca_topic_score_gemma":0.002948057,"domain_scores_codex":[0.9981455,0.0005635637,0.0001144146,0.0003118709,0.0008009388,0.00006377538],"domain_scores_gemma":[0.996485,0.002292968,0.00008928071,0.000493066,0.0005842931,0.00005534116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002284077,0.0001055475,0.0003020312,0.0007466567,0.00009616834,0.00009580511,0.0001768227,0.005740079,0.0006336591,0.3260446,0.2927902,0.3732455],"study_design_scores_gemma":[0.00001852469,0.00002421729,0.0005272613,0.0004028241,0.00004619402,0.0004436047,0.00005427704,0.01794477,0.000718424,0.4470897,0.5326685,0.00006175927],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005472854,0.05632017,0.8237126,0.001825769,0.00173285,0.0001252219,0.001995056,0.003062288,0.1106788],"genre_scores_gemma":[0.02333393,0.06472132,0.7447082,0.001775101,0.00346363,0.0007198854,0.005798233,0.003341255,0.1521385],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05389863,"threshold_uncertainty_score":0.1803089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04445392640031894,"score_gpt":0.3518999870833702,"score_spread":0.3074460606830512,"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."}}