{"id":"W2204774351","doi":"10.1080/01621459.2015.1108848","title":"Exact Post-Selection Inference for Sequential Regression Procedures","year":2016,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":352,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Inference; Lasso (programming language); Mathematics; Regression; Model selection; Algorithm; Regularization (linguistics); Computer science; Regression analysis; Statistics; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.001053104,0.0001227362,0.0003611492,0.00005508399,0.0001227757,0.00004013132,0.0001939782,0.00004966846,0.00008081631],"category_scores_gemma":[0.06485523,0.00005739568,0.000124682,0.0001735071,0.000103503,0.0001096233,0.00003465774,0.0001640909,0.000003943218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004068829,"about_ca_system_score_gemma":0.0002311955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001692925,"about_ca_topic_score_gemma":0.00001489513,"domain_scores_codex":[0.998162,0.0003895267,0.0005562366,0.000125189,0.0005264232,0.000240576],"domain_scores_gemma":[0.9874521,0.009615554,0.001840702,0.0001002168,0.0009008011,0.00009059634],"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":[0.001390373,0.0004434844,0.04400467,0.0001685872,0.0003560597,0.000004569664,0.0002951822,0.000004028444,0.09993327,0.4278401,0.05205883,0.3735008],"study_design_scores_gemma":[0.0009398409,0.001309715,0.1276315,0.0003380783,0.0002451776,0.00002326099,0.00007477774,0.0003955003,0.005019916,0.8628704,0.0009336533,0.0002182112],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1104689,0.000005273164,0.8855568,0.003237461,0.0003042068,0.0001760207,0.0001569068,0.00001447147,0.00007990083],"genre_scores_gemma":[0.7468515,0.0000213918,0.2523272,0.0001988057,0.0002734414,0.000009415042,7.453452e-7,0.00001547464,0.0003020498],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6363826,"threshold_uncertainty_score":0.9430219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04245338162808755,"score_gpt":0.4014923890323961,"score_spread":0.3590390074043086,"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."}}