{"id":"W2949372305","doi":"10.1080/01621459.2019.1632078","title":"Model-Free Forward Screening Via Cumulative Divergence","year":2019,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Institute on Drug Abuse; National Natural Science Foundation of China","keywords":"Divergence (linguistics); Mathematics; Statistics","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":[0.001258837,0.0001353499,0.0004952992,0.00004892403,0.00008850397,0.00003554155,0.0004495105,0.00004197709,0.000146017],"category_scores_gemma":[0.01483793,0.00008835458,0.0001485372,0.0002684817,0.00008998817,0.0001150744,0.0001559966,0.000395569,0.00001787484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002743388,"about_ca_system_score_gemma":0.00006850464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003523006,"about_ca_topic_score_gemma":0.000004549442,"domain_scores_codex":[0.997641,0.0004018741,0.0006318333,0.0001342381,0.0009225932,0.000268428],"domain_scores_gemma":[0.9921436,0.00514622,0.00187578,0.0002620408,0.0004608719,0.0001114801],"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":[0.000557646,0.0003927638,0.1880115,0.00009446032,0.0007484119,0.00001465076,0.001092619,0.003561329,0.003194985,0.6600427,0.03623382,0.1060551],"study_design_scores_gemma":[0.0003949087,0.0002555252,0.08277652,0.00004922675,0.000136653,0.000005884566,0.00008941212,0.1367572,0.0001001819,0.7791967,0.00009936632,0.0001384349],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1097529,0.000005287267,0.8882849,0.00073992,0.0002293808,0.0001192977,0.0001065891,0.00001004569,0.0007516517],"genre_scores_gemma":[0.4921958,0.000004880638,0.5071394,0.0002337449,0.00006574232,0.000001300369,5.095471e-7,0.0000121646,0.0003464217],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3824429,"threshold_uncertainty_score":0.9934605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05327451455521445,"score_gpt":0.3651657928124792,"score_spread":0.3118912782572647,"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."}}