{"id":"W3015662163","doi":"10.1111/biom.13277","title":"A powerful procedure that controls the false discovery rate with directional information","year":2020,"lang":"en","type":"article","venue":"Biometrics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"False discovery rate; Multiple comparisons problem; Computer science; Statistical hypothesis testing; Data mining; Control (management); Value (mathematics); Statistics; Computational biology; Machine learning; Artificial intelligence; Mathematics; Biology; Gene; Genetics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001814599,0.0001695297,0.0003676458,0.0002013278,0.0000960757,0.0002451779,0.000270375,0.000113436,0.00007450877],"category_scores_gemma":[0.1312115,0.00009193143,0.00009272483,0.00278558,0.0001425258,0.0004251367,0.0000793209,0.0002413255,0.00009209076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004115747,"about_ca_system_score_gemma":0.0000968636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003732724,"about_ca_topic_score_gemma":9.190322e-7,"domain_scores_codex":[0.998173,0.0003107236,0.0005095459,0.0001946511,0.0005876894,0.0002244053],"domain_scores_gemma":[0.9701871,0.02888308,0.0003669829,0.0002386149,0.0001878039,0.0001364217],"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":[0.007349657,0.001299777,0.0232344,0.002332858,0.001798219,0.00006158236,0.003761598,0.00008051663,0.002352244,0.6720681,0.1788289,0.1068322],"study_design_scores_gemma":[0.01127242,0.002716471,0.03202861,0.0002422442,0.0008539206,0.00004795885,0.001623905,0.003968596,0.007876395,0.7914894,0.146294,0.001586096],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02567324,0.0001399896,0.95836,0.01023024,0.000684667,0.001555023,0.0004762547,0.0002417924,0.002638791],"genre_scores_gemma":[0.5780051,0.0000846176,0.4127257,0.007774999,0.0007594168,0.0001171141,0.00001816163,0.00005491314,0.0004599883],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5523319,"threshold_uncertainty_score":0.8761067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3902658894803887,"score_gpt":0.46597937872472,"score_spread":0.0757134892443313,"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."}}