{"id":"W274425175","doi":"10.1002/cjs.5550330401","title":"A nonparametric procedure for the analysis of balanced crossover designs","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Mathematics; Nonparametric statistics; Combinatorics; Permutation (music); Estimator; Crossover; Statistics; Limiting; Computer science; Engineering; Artificial intelligence; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002870793,0.0001124486,0.0004636281,0.001135621,0.0001640525,0.0002001502,0.0007924558,0.00005765693,0.0005994989],"category_scores_gemma":[0.01126349,0.00007090878,0.0002218924,0.002722119,0.0002296855,0.0001728624,0.00001132589,0.0001407795,0.0000080488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001620596,"about_ca_system_score_gemma":0.001280714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003850988,"about_ca_topic_score_gemma":0.005461044,"domain_scores_codex":[0.9978176,0.0001278874,0.000924626,0.0001530123,0.0006991389,0.0002777176],"domain_scores_gemma":[0.9920995,0.005204804,0.0007809906,0.0002836603,0.001232142,0.0003988561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007246692,0.0001817125,0.04827003,0.00003714072,0.0036885,0.0001120875,0.007480572,0.2205412,0.005629468,0.03583693,0.2762047,0.401293],"study_design_scores_gemma":[0.003530157,0.001540825,0.2953344,0.00006608591,0.004252352,0.000147707,0.004581053,0.5435454,0.009878039,0.03137822,0.1048819,0.0008638366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01589592,0.001014217,0.9810505,0.0003843625,0.0002550621,0.0002126593,0.0009006554,0.000001500565,0.000285117],"genre_scores_gemma":[0.6044075,0.000009185991,0.3948986,0.0002256025,0.00006480562,0.000002818644,0.000001652585,0.000008150951,0.0003816831],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5885116,"threshold_uncertainty_score":0.9970651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1650089379367188,"score_gpt":0.4316667355078029,"score_spread":0.2666577975710841,"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."}}