{"id":"W2953107438","doi":"10.1371/journal.pgen.1006235","title":"Accelerating Gene Discovery by Phenotyping Whole-Genome Sequenced Multi-mutation Strains and Using the Sequence Kernel Association Test (SKAT)","year":2016,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Universities Space Research Association; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Biology; Genetic screen; Genetics; Gene; Forward genetics; Phenotype; Computational biology; Mutation; Genome","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00371948,0.001884775,0.001631136,0.003045493,0.0005306347,0.001141152,0.001057858,0.001139421,0.003697006],"category_scores_gemma":[0.003833469,0.0006183043,0.002295206,0.001954849,0.0008865399,0.0006949158,0.001824922,0.001819973,0.002066341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002903224,"about_ca_system_score_gemma":0.0005984633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005345548,"about_ca_topic_score_gemma":0.001383641,"domain_scores_codex":[0.9981967,0.0005205494,0.0002102576,0.0005590819,0.0003901762,0.0001232794],"domain_scores_gemma":[0.9931393,0.004812596,0.0009565556,0.0005487183,0.0002721337,0.000270581],"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":[0.0006587578,0.0003434646,0.01420889,0.001034869,0.0006511929,0.0009632565,0.0001552667,0.003978095,0.9033701,0.002141323,0.001037492,0.0714573],"study_design_scores_gemma":[0.0004112735,0.002813801,0.07616463,0.0001614891,0.001027283,0.006276321,0.0002131657,0.09086559,0.7906399,0.007916701,0.02319726,0.0003125681],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2269201,0.0007423384,0.7510399,0.0003622906,0.0001270633,0.0005815614,0.008087362,0.01041927,0.001720191],"genre_scores_gemma":[0.3027763,0.001582435,0.677377,0.0004090585,0.00004872992,0.00111795,0.01239679,0.001871499,0.002420266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00371948,"threshold_uncertainty_score":0.01967072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04166997432963382,"score_gpt":0.2627217182652908,"score_spread":0.221051743935657,"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."}}