{"id":"W4411171489","doi":"10.1371/journal.pgen.1011730","title":"A mathematical framework for the quantitative analysis of genetic buffering","year":2025,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Evolutionary biology; Computational biology; Genetics","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":[0.0002274919,0.0001204774,0.0003025933,0.00009475896,0.00009679719,0.00001041393,0.0002621657,0.0001703048,0.00001999869],"category_scores_gemma":[0.0009983091,0.00009272256,0.0002356629,0.0003880028,0.0001118257,5.437655e-7,0.0001028077,0.00006496761,0.000002052522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001139649,"about_ca_system_score_gemma":0.0000584479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002488789,"about_ca_topic_score_gemma":0.00002085384,"domain_scores_codex":[0.9990141,0.00006950655,0.0003759365,0.0002413034,0.00008606754,0.0002131085],"domain_scores_gemma":[0.9985971,0.0006026597,0.0001421444,0.0004558483,0.0001719336,0.000030355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003806674,0.001048244,0.4773454,0.000518661,0.0366756,0.000001208911,0.001451828,0.1234826,0.229654,0.115183,0.004582715,0.009676038],"study_design_scores_gemma":[0.0008615284,0.0007873779,0.2799326,0.00008320727,0.009550712,0.000001409551,0.001344215,0.5636323,0.0664304,0.07121067,0.005597922,0.0005675714],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4907238,0.002041613,0.5063447,0.0003220867,0.00005976136,0.0002470722,0.00003439439,0.000004419467,0.0002221791],"genre_scores_gemma":[0.8790863,0.0003469276,0.1199432,0.0002688482,0.00004390641,0.00009965513,0.00002621092,0.00001180748,0.0001731389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4401498,"threshold_uncertainty_score":0.3781116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430574523805078,"score_gpt":0.3385693591837491,"score_spread":0.3042636139456983,"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."}}