{"id":"W2802587671","doi":"10.1371/journal.pgen.1007306","title":"One for all and all for One: Improving replication of genetic studies through network diffusion","year":2018,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Institute of Mental Health; National Institute on Aging; National Center for Advancing Translational Sciences; University of Southern California; Wellcome Trust; National Human Genome Research Institute; University of California, San Diego; National Institutes of Health; National Center for Research Resources; University of Pennsylvania; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; Canadian Institutes of Health Research; Foundation for the National Institutes of Health","keywords":"Genome-wide association study; Biology; Computational biology; Genetic association; Replication (statistics); Disease; Biological network; Gene regulatory network; Genome; Gene; Genetics; Computer science; Bioinformatics; Single-nucleotide polymorphism; Medicine; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001879632,0.0001490731,0.0002257622,0.00001514094,0.0001042161,0.00001668772,0.0001516697,0.0001661213,0.000001356369],"category_scores_gemma":[0.00008073148,0.0001536945,0.00006604213,0.00003829387,0.0001493249,0.000003188173,0.000182819,0.00003893388,7.516001e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001060657,"about_ca_system_score_gemma":0.00002813415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001920671,"about_ca_topic_score_gemma":0.00002730699,"domain_scores_codex":[0.9988585,0.00001515216,0.0003925851,0.0003511838,0.00008740738,0.0002951551],"domain_scores_gemma":[0.9988527,0.00004244152,0.0002416304,0.0005271651,0.0002847472,0.00005130405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002778706,0.0001723455,0.0006649464,0.0005996595,0.0007965774,5.007819e-8,0.0008083126,0.0001491462,0.959317,0.0004377165,0.004051302,0.03272506],"study_design_scores_gemma":[0.003288211,0.005629055,0.001444241,0.0001820899,0.000936604,0.000005840401,0.0002861983,0.08406719,0.8197163,0.022516,0.06101748,0.0009107855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8991473,0.01083946,0.0878696,0.0002577355,0.0002089381,0.001477861,0.00006371058,0.00001435885,0.0001210725],"genre_scores_gemma":[0.7417765,0.004447758,0.2507445,0.0008816821,0.001623432,0.0001786053,0.0001837824,0.00005137362,0.0001123872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1628749,"threshold_uncertainty_score":0.626748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04632189524710151,"score_gpt":0.2924722626829123,"score_spread":0.2461503674358108,"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."}}