{"id":"W2953112128","doi":"10.1186/s13059-018-1545-7","title":"Modularity of genes involved in local adaptation to climate despite physical linkage","year":2018,"lang":"en","type":"article","venue":"Genome biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"College of Agriculture and Life Sciences, Virginia Polytechnic Institute and State University; Division of Environmental Biology; Genome Alberta; University of British Columbia; Alberta Innovates Bio Solutions; Ministry of Forests, Lands and Natural Resource Operations; Genome British Columbia; Alberta Innovates; Forest Genetics Council of British Columbia; Genome Canada; National Science Foundation","keywords":"Biology; Pleiotropy; Local adaptation; Pinus contorta; Adaptation (eye); Genetic architecture; Modularity (biology); Genetics; Selection (genetic algorithm); Evolutionary biology; Natural selection; Linkage (software); Balancing selection; Gene; Candidate gene; Computational biology; Allele; Quantitative trait locus; Ecology; Population; Phenotype","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":[0.0005485793,0.0002779498,0.0002711458,0.000831829,0.0003940433,0.0007225922,0.00036221,0.0003807788,0.001068561],"category_scores_gemma":[0.001865822,0.0001472623,0.0002956091,0.0007503286,0.0009135289,0.0005645671,0.0006062519,0.0003154604,0.0001272077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004141514,"about_ca_system_score_gemma":0.0002489651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009326195,"about_ca_topic_score_gemma":0.001099225,"domain_scores_codex":[0.9997616,0.00003743657,0.00001161144,0.0001239738,0.00003477519,0.00003058157],"domain_scores_gemma":[0.9985549,0.0006261361,0.0004450547,0.0001234644,0.0001063187,0.0001441439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009141235,0.0001168808,0.4853182,0.0004592786,0.000678018,0.001223245,0.0012126,0.03640606,0.4057623,0.02157305,0.0007364063,0.04559976],"study_design_scores_gemma":[0.00007122367,0.0001839862,0.8238504,0.00005581706,0.0005100119,0.00162562,0.0004013315,0.1027902,0.02882743,0.03957106,0.002046585,0.00006638333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903336,0.0002610756,0.008318557,0.00008879595,0.000004519396,0.000008658771,0.0001400521,0.00007891772,0.0007658654],"genre_scores_gemma":[0.9981952,0.00003295024,0.001570515,0.00001254392,0.00000391952,0.000005891409,0.00006828399,0.000007539159,0.0001031655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001068561,"threshold_uncertainty_score":0.003574669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949774506673401,"score_gpt":0.2613186195745796,"score_spread":0.2418208745078456,"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."}}