{"id":"W2101234197","doi":"10.1093/biomet/asq001","title":"Mean loglikelihood and higher-order approximations","year":2010,"lang":"en","type":"article","venue":"Biometrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Library science; Order (exchange); Mathematics; Statistics; Demography; Computer science; Sociology; Economics","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":[0.01071309,0.001168482,0.001799308,0.00277978,0.0008093251,0.004175295,0.003892677,0.002575875,0.00700547],"category_scores_gemma":[0.1005036,0.0009788764,0.001604997,0.002863424,0.003496324,0.006567817,0.002539202,0.005192377,0.002234758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003158722,"about_ca_system_score_gemma":0.002074244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004717872,"about_ca_topic_score_gemma":0.003926382,"domain_scores_codex":[0.9933926,0.003542685,0.0002879371,0.0008718924,0.0015108,0.000394055],"domain_scores_gemma":[0.9437209,0.0483529,0.001530152,0.004177931,0.001837924,0.0003802225],"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":[0.00005349303,0.00002532781,0.001066892,0.000163144,0.00006631298,0.0002020167,0.0002272462,0.2024807,0.0004394541,0.7609452,0.003528163,0.03080207],"study_design_scores_gemma":[0.000008977947,0.00001254932,0.0003810845,0.00005551136,0.00001333237,0.0001925178,0.00003630314,0.3769839,0.0003351926,0.6193509,0.002602824,0.00002688858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003835805,0.0008380765,0.9913567,0.0005255952,0.00005283817,0.00001267377,0.0001147705,0.0002040072,0.003059423],"genre_scores_gemma":[0.4341569,0.004590952,0.5372412,0.001095955,0.0007387146,0.0003976206,0.001103231,0.0008807741,0.01979481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01071309,"threshold_uncertainty_score":0.0566569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0579463933337299,"score_gpt":0.3552655433629575,"score_spread":0.2973191500292275,"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."}}