{"id":"W2754449371","doi":"10.1186/s40488-017-0076-1","title":"Rank correlation under categorical confounding","year":2017,"lang":"en","type":"article","venue":"Journal of Statistical Distributions and Applications","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Mathematics; Confounding; Categorical variable; Statistics; Correlation; Weighting; Invariant (physics); Bijection; Rank correlation; Applied mathematics; Combinatorics; Physics","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":[0.0004384289,0.00009996942,0.0002512737,0.00003675923,0.000752697,0.0001861665,0.0001814429,0.00006636389,0.0001589503],"category_scores_gemma":[0.0027553,0.0000797258,0.00004699585,0.00005544296,0.0004890977,0.000128857,0.00004916434,0.0002476215,0.00001000533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005020112,"about_ca_system_score_gemma":0.00006515739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001159722,"about_ca_topic_score_gemma":0.0000015046,"domain_scores_codex":[0.9989721,0.00005355923,0.000495582,0.0001217728,0.0001966534,0.0001603983],"domain_scores_gemma":[0.9970397,0.001733792,0.0004378604,0.000242444,0.0003434476,0.0002027039],"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":[0.00001006346,0.00008829046,0.0004314893,0.00001551635,0.00002084244,0.000003526233,0.00001226152,0.000001275658,0.00006293239,0.9842892,0.001721371,0.0133432],"study_design_scores_gemma":[0.0003477114,0.00006030995,0.04004302,0.00001885272,0.0001150566,0.00007767036,0.000113219,0.001095366,0.00001724591,0.9541352,0.003880781,0.00009554753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002758964,0.00005043609,0.9939473,0.0007056381,0.00008632412,0.0001351232,0.0003603948,0.000009568561,0.001946255],"genre_scores_gemma":[0.8438937,0.00006185463,0.1557898,0.0000209808,0.0001442514,0.0000191502,0.00001633737,0.000006873463,0.0000470136],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8411347,"threshold_uncertainty_score":0.5789213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08315590565256163,"score_gpt":0.4214123968668709,"score_spread":0.3382564912143092,"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."}}