{"id":"W3084047481","doi":"10.1093/ectj/utab013","title":"Exact Computation of Maximum Rank Correlation Estimator","year":2021,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Estimator; Solver; Rank (graph theory); Computation; Mathematics; Mathematical optimization; Monte Carlo method; Binary number; Applied mathematics; Algorithm; Statistics; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005859544,0.001217031,0.001972022,0.002144649,0.0007825952,0.002612642,0.002282658,0.001738863,0.01119005],"category_scores_gemma":[0.056798,0.0009816422,0.001021695,0.002262183,0.001752619,0.004823959,0.003426501,0.002449836,0.003332969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001034069,"about_ca_system_score_gemma":0.002794438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001460434,"about_ca_topic_score_gemma":0.002796225,"domain_scores_codex":[0.9946808,0.002931278,0.0002483821,0.0006396603,0.00117311,0.000326792],"domain_scores_gemma":[0.971939,0.02038645,0.001179179,0.003731617,0.002271944,0.0004918182],"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":[0.0005310754,0.00019002,0.003040004,0.0007857593,0.0002402977,0.0005917979,0.0002971956,0.2208118,0.006376617,0.5334325,0.0172735,0.2164294],"study_design_scores_gemma":[0.00004763177,0.00005487253,0.0007305437,0.00006917466,0.00003759437,0.0002701817,0.00004873957,0.7265854,0.003290519,0.2651895,0.003629953,0.00004569102],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005888533,0.000421522,0.990505,0.0002431867,0.0000805075,0.00002846165,0.0001527916,0.0004549998,0.002224988],"genre_scores_gemma":[0.2850207,0.0008370007,0.7020652,0.0003461054,0.0004192048,0.0002758583,0.0009817227,0.0008212568,0.009233022],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01119005,"threshold_uncertainty_score":0.03743446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1842590734932299,"score_gpt":0.419174956068803,"score_spread":0.2349158825755731,"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."}}