{"id":"W2748169160","doi":"10.1111/insr.12230","title":"Stratification of Skewed Populations: A Comparison of Optimisation‐based versus Approximate Methods","year":2017,"lang":"en","type":"article","venue":"International Statistical Review","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Estimator; Mathematics; Flexibility (engineering); Mathematical optimization; Population; Stratum; Computer science; Statistics; Stratification (seeds); Sample size determination; Econometrics; Engineering","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001123293,0.0001448823,0.0005907537,0.00005679596,0.0001004352,0.00004453119,0.0005196374,0.0000579608,0.001135148],"category_scores_gemma":[0.02939811,0.0001250359,0.00009670868,0.00006817231,0.0002524935,0.0001066032,0.00006003357,0.0001231549,0.000007011533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004369935,"about_ca_system_score_gemma":0.00007533374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004373387,"about_ca_topic_score_gemma":0.000008159016,"domain_scores_codex":[0.9977457,0.0003096833,0.001101928,0.000230406,0.0004831581,0.0001291357],"domain_scores_gemma":[0.9941284,0.00360439,0.001121805,0.000548287,0.0005206338,0.00007647333],"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":[0.00004986643,0.000162278,0.0002607691,0.0009886333,0.00003662407,5.459224e-7,0.00001458354,0.000002136522,0.0001543325,0.7914726,0.0004646897,0.2063929],"study_design_scores_gemma":[0.0007217262,0.0001441539,0.006466096,0.002021211,0.0002573435,0.000001013096,0.00001462383,0.04403771,0.001612797,0.9436544,0.0008732678,0.000195634],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005657849,0.0005606096,0.9921057,0.0006250427,0.0003552767,0.0003741928,0.0003338452,0.0000166941,0.005572074],"genre_scores_gemma":[0.06866555,0.0002400978,0.930874,0.00002828512,0.0000271168,0.00004986743,0.00008457659,0.00001212944,0.00001841406],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2061973,"threshold_uncertainty_score":0.999778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4317204470670315,"score_gpt":0.6023179494079958,"score_spread":0.1705975023409643,"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."}}