{"id":"W3204449925","doi":"10.1002/sim.9211","title":"Two‐phase sample selection strategies for design and analysis in post‐genome‐wide association fine‐mapping studies","year":2021,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Princess Margaret Cancer Centre; Public Health Ontario; University of Toronto; University Health Network","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; Terveyden ja hyvinvoinnin laitos; Oulun Yliopisto; Government of Ontario; Broad Institute; Compute Canada; University of Toronto; Ontario Institute for Cancer Research","keywords":"Selection (genetic algorithm); Sample (material); Computer science; Sample size determination; Genome-wide association study; Genetic association; Association (psychology); Statistics; Biology; Genetics; Mathematics; Artificial intelligence; Psychology; Single-nucleotide polymorphism; Genotype; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.000485299,0.0001096729,0.000258375,0.0001166415,0.00005007369,0.00001143684,0.00004461656,0.00006689748,0.00001696946],"category_scores_gemma":[0.002782444,0.0001066375,0.000019338,0.0003070459,0.00005349062,0.000003181464,0.00002495206,0.00007585462,1.739911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004709417,"about_ca_system_score_gemma":0.0001252207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006746128,"about_ca_topic_score_gemma":0.00164283,"domain_scores_codex":[0.9990523,0.0001168536,0.0002823473,0.0002634854,0.0001046398,0.0001803783],"domain_scores_gemma":[0.9988239,0.0007017743,0.00009603343,0.00009306459,0.0002516863,0.0000335083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001430086,0.001271335,0.3846227,0.001020055,0.007555475,0.00003807472,0.02031405,0.1827008,0.2586886,0.08931506,0.01358613,0.03945766],"study_design_scores_gemma":[0.01515141,0.004520885,0.6764227,0.0001541,0.001473662,0.000009306868,0.01996532,0.01047456,0.004136752,0.2631853,0.003574398,0.0009315746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.179304,0.001691101,0.8183485,0.0002432333,0.00008025454,0.0001722011,0.0001183772,0.000003520283,0.00003880335],"genre_scores_gemma":[0.5058699,0.0003292238,0.4924906,0.0002307035,0.0001303137,0.00004203186,0.000749976,0.00001047773,0.0001467999],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3265659,"threshold_uncertainty_score":0.4348551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02981557015360321,"score_gpt":0.3370308187222602,"score_spread":0.307215248568657,"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."}}