{"id":"W2989760732","doi":"10.1111/pbi.13299","title":"Learning from methylomes: epigenomic correlates of <i>Populus balsamifera</i> traits based on deep learning models of natural DNA methylation","year":2019,"lang":"en","type":"article","venue":"Plant Biotechnology Journal","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of British Columbia; University of Guelph; The Scarborough Hospital; University of Toronto","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; University of Guelph; Genome Canada","keywords":"Biology; DNA methylation; Epigenetics; Epigenomics; Population; Quantitative trait locus; Natural population growth; Genetic variation; Methylation; Genetics; Evolutionary biology; DNA; Gene; Computational biology; Gene expression","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":[0.0002963657,0.0002928575,0.0001675532,0.0001976362,0.00009718275,0.0002736223,0.000250233,0.0002181757,0.0004908424],"category_scores_gemma":[0.0007211397,0.0001341294,0.0002489793,0.0002002046,0.0001758572,0.0002946648,0.0002887108,0.0004142598,0.0001231032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002101266,"about_ca_system_score_gemma":0.0001480501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002007414,"about_ca_topic_score_gemma":0.003818958,"domain_scores_codex":[0.9999408,0.0000184309,0.000001560473,0.00002605838,0.000005983233,0.000007235709],"domain_scores_gemma":[0.9998009,0.0000963761,0.00005206577,0.000020929,0.00001554018,0.00001427353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009791409,0.0003520881,0.2117526,0.0002190992,0.0007493465,0.0001996213,0.0002781052,0.2710792,0.3473799,0.00316955,0.0008528129,0.1629885],"study_design_scores_gemma":[0.00002255311,0.0002176814,0.1491427,0.00001655959,0.0001071617,0.0001222315,0.0000639821,0.8049622,0.03578785,0.008294295,0.001226773,0.00003616044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.90131,0.0002919821,0.0967776,0.0001090367,0.000008687263,0.00001324147,0.0006144252,0.0002419882,0.0006329721],"genre_scores_gemma":[0.9861644,0.0001097303,0.01254225,0.00003098774,0.000005547758,0.00001408479,0.0006458702,0.00002052813,0.0004666861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002007414,"threshold_uncertainty_score":0.003991485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153958888068139,"score_gpt":0.1910208099685178,"score_spread":0.1756249211617039,"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."}}