{"id":"W2091723435","doi":"10.1016/j.stamet.2010.07.004","title":"An odd property of sample median from odd sample sizes","year":2010,"lang":"en","type":"article","venue":"Statistical Methodology","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Sample (material); Counterexample; Sample size determination; Statistics; Sample mean and sample covariance; Closeness; Property (philosophy); Distribution (mathematics); Population; Large sample; Probabilistic logic; Combinatorics; Demography; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002414091,0.0002186446,0.0006213267,0.00009443703,0.00008924198,0.00004842704,0.001098792,0.0002603766,0.0008310283],"category_scores_gemma":[0.01205432,0.0001472084,0.00006608794,0.0002126465,0.0004301274,0.0001990037,0.0002116403,0.0005080473,0.0000144507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001035253,"about_ca_system_score_gemma":0.0001549664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003705274,"about_ca_topic_score_gemma":0.0008061273,"domain_scores_codex":[0.9956545,0.002419417,0.0004810551,0.0007104777,0.000257786,0.0004768198],"domain_scores_gemma":[0.9779286,0.02039939,0.0001418969,0.001022996,0.0001498695,0.0003572276],"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":[0.00002428381,0.00006231422,0.0002448605,0.0000103637,0.0000167402,0.000007959854,0.0004268066,6.890018e-7,0.02700785,0.5057856,0.0002075873,0.4662049],"study_design_scores_gemma":[0.0002994973,0.0003061701,0.004282139,0.00000540228,0.00002420247,0.00001034887,0.00001433544,0.0169073,0.009731036,0.9658348,0.00235738,0.0002273679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001976133,0.0000281382,0.9946506,0.0008210069,0.001206778,0.0001789826,0.0006449549,0.00009900263,0.0003943848],"genre_scores_gemma":[0.02819949,0.000007452047,0.9709492,0.0005135844,0.0002264377,0.00001919288,0.00004798372,0.0000192461,0.00001741447],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4659775,"threshold_uncertainty_score":0.9962676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0930813728022253,"score_gpt":0.3770364275727918,"score_spread":0.2839550547705665,"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."}}