{"id":"W4229715815","doi":"10.1038/npre.2011.5162.2","title":"Principles for the post-GWAS functional characterisation of risk loci","year":2011,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Diamantina Institute, University of Queensland; Illawarra Health and Medical Research Institute; Tampereen Yliopisto; Karolinska Institutet; Università degli Studi di Trento; University of Dundee; Queen Mary University of London; University of Queensland; Universitat Pompeu Fabra; National Institutes of Health; Queen's University; Royal Marsden NHS Foundation Trust; Wellcome Trust; Dartmouth College; University of Wollongong; Child and Family Research Institute; University of Texas at Austin","keywords":"Genome-wide association study; Computational biology; Single-nucleotide polymorphism; Computer science; Biology; Genetics; Gene; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02307694,0.001545659,0.001916681,0.003508008,0.001709953,0.004907513,0.005254147,0.002392027,0.003890899],"category_scores_gemma":[0.02255582,0.001521493,0.002819002,0.001707154,0.007546626,0.00550975,0.004177665,0.005846007,0.003646867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001934005,"about_ca_system_score_gemma":0.002700006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002385926,"about_ca_topic_score_gemma":0.002187955,"domain_scores_codex":[0.9937757,0.00274253,0.0005156591,0.001284705,0.001403574,0.0002777486],"domain_scores_gemma":[0.9813299,0.008074584,0.001194247,0.005804491,0.002926442,0.0006702469],"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":[0.0001998785,0.000304406,0.005171368,0.0009122146,0.0002698143,0.000409943,0.00103741,0.02173465,0.04446321,0.7560633,0.005733763,0.1637002],"study_design_scores_gemma":[0.00004888066,0.0001321546,0.002744493,0.0001022249,0.00006295416,0.0001978566,0.0001476991,0.06448369,0.008242962,0.9089918,0.01475636,0.00008893035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002064787,0.0002356682,0.9954101,0.0008179614,0.00005568243,0.00007926599,0.00008069129,0.0003447439,0.000911104],"genre_scores_gemma":[0.04357562,0.0003612865,0.9533321,0.0005647639,0.0001391788,0.0003340949,0.0002116334,0.0002500321,0.001231406],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02307694,"threshold_uncertainty_score":0.122044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02119673261889259,"score_gpt":0.2471273036016139,"score_spread":0.2259305709827213,"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."}}