{"id":"W2167841915","doi":"10.1111/insr.12064","title":"Small‐scale Inference: Empirical Bayes and Confidence Methods for as Few as a Single Comparison","year":2014,"lang":"en","type":"preprint","venue":"International Statistical Review","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Canada Foundation for Innovation; University of Ottawa","keywords":"Inference; Statistics; Confidence interval; Null hypothesis; Bayes' theorem; Null (SQL); False discovery rate; Mathematics; Econometrics; Statistical inference; Group (periodic table); Multiple comparisons problem; Biology; Computer science; Bayesian probability; Artificial intelligence; Data mining; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007729301,0.00066046,0.002876423,0.00009871995,0.000101378,0.0002932675,0.001073914,0.0005768543,0.00262612],"category_scores_gemma":[0.5079486,0.0005612549,0.0003885042,0.0001099398,0.0006049844,0.0000471472,0.001220186,0.001230089,0.000153366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001841567,"about_ca_system_score_gemma":0.0003142768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006029783,"about_ca_topic_score_gemma":0.00001578255,"domain_scores_codex":[0.9915569,0.002725293,0.003021503,0.001354175,0.000832402,0.0005096665],"domain_scores_gemma":[0.7913612,0.2054183,0.001117237,0.0006958081,0.0009049209,0.0005024987],"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":[0.0001235333,0.0003540812,0.0001014489,0.007647353,0.0002639636,0.000008862941,0.00004566687,0.00000129347,0.00001564057,0.6103173,0.01253706,0.3685838],"study_design_scores_gemma":[0.0005000997,0.000384319,0.0001207644,0.008557439,0.0007099792,0.00002316815,0.000008989849,0.004557331,0.00008497833,0.9082012,0.07630298,0.0005487343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009062916,0.007307811,0.9784315,0.004369885,0.001752327,0.002284645,0.001005718,0.0001188676,0.004638597],"genre_scores_gemma":[0.001433069,0.008292763,0.9847265,0.00363513,0.0005220117,0.000799701,0.0001258182,0.00008281167,0.00038217],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5002193,"threshold_uncertainty_score":0.9996839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7750999583842813,"score_gpt":0.7121616343933252,"score_spread":0.062938323990956,"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."}}