{"id":"W1503357936","doi":"10.1111/biom.12006","title":"A Generalized Kruskal–Wallis Test Incorporating Group Uncertainty with Application to Genetic Association Studies","year":2013,"lang":"en","type":"article","venue":"Biometrics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Ontario; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Mathematics; Kruskal–Wallis one-way analysis of variance; Statistics; Kruskal's algorithm; Test statistic; Null hypothesis; Generalization; Robustness (evolution); Pearson's chi-squared test; Statistic; Statistical hypothesis testing; Combinatorics; Mann–Whitney U test; Genetics; Spanning tree; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004904552,0.000186982,0.0002587423,0.0002928,0.0001488055,0.00004251762,0.0001847177,0.0002097244,0.000008561393],"category_scores_gemma":[0.002933468,0.0001573913,0.00005793216,0.001575838,0.00003617858,0.00000548068,0.0001212308,0.00006749688,0.00008021605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001959653,"about_ca_system_score_gemma":0.00004900076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003395937,"about_ca_topic_score_gemma":0.0001824427,"domain_scores_codex":[0.9985376,0.0001023777,0.0003649714,0.0004343964,0.0002213079,0.0003393211],"domain_scores_gemma":[0.9984086,0.0002382703,0.0003537319,0.0003220223,0.0005539256,0.0001234743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001587929,0.0001517164,0.7804564,0.00002388341,0.0002446614,6.727395e-7,0.00008710894,0.002140103,0.1708722,0.00008525775,0.02466778,0.02125431],"study_design_scores_gemma":[0.001370906,0.001633266,0.9479452,0.00001785096,0.0001131023,0.000007940042,0.0004628618,0.003444987,0.003166088,0.000801901,0.04025146,0.0007844249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700397,0.0008675287,0.026924,0.001202709,0.0001083662,0.0006475214,0.00002866981,0.00002999409,0.0001515382],"genre_scores_gemma":[0.9467166,0.0002762997,0.05042128,0.001119394,0.0002720589,0.0004204161,0.0001941542,0.00002589701,0.000553912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1677061,"threshold_uncertainty_score":0.6418232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714515962455231,"score_gpt":0.2755852198901973,"score_spread":0.258440060265645,"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."}}