{"id":"W3084260795","doi":"10.3390/f11090976","title":"Advances and Promises of Epigenetics for Forest Trees","year":2020,"lang":"en","type":"article","venue":"Forests","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Outaouais","funders":"Centro de Estudos Ambientais e Marinhos, Universidade de Aveiro; Fundação para a Ciência e a Tecnologia; Ministério da Ciência, Tecnologia e Ensino Superior; Agence Nationale de la Recherche","keywords":"Epigenetics; Tree (set theory); Adaptation (eye); Field (mathematics); Forest management; Biology; Ecology; Environmental resource management; Neuroscience","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002495741,0.0003412445,0.0006831721,0.001661911,0.000740465,0.002164909,0.0005147844,0.001349468,0.003787782],"category_scores_gemma":[0.002817713,0.0001819961,0.0004755648,0.001401371,0.002583819,0.005562273,0.00118696,0.00239853,0.0006513082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001158924,"about_ca_system_score_gemma":0.001706021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001060431,"about_ca_topic_score_gemma":0.001875721,"domain_scores_codex":[0.999524,0.0001537183,0.00004743042,0.0001145029,0.0001225622,0.00003778293],"domain_scores_gemma":[0.9964591,0.002709492,0.0002119287,0.0001403685,0.0003234259,0.0001557408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001934815,0.0000515344,0.002993201,0.008940838,0.0001203805,0.0004967445,0.001682371,0.0009060334,0.01483512,0.1341005,0.01419227,0.8214875],"study_design_scores_gemma":[0.000007891311,0.0001090748,0.006307729,0.002854396,0.0001321326,0.0007162687,0.00140752,0.0004794879,0.005431787,0.1096272,0.8728479,0.00007868229],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002906758,0.967433,0.00455451,0.01757415,0.001056432,0.000007465777,0.0001255598,0.00004172957,0.006300356],"genre_scores_gemma":[0.03701032,0.9487682,0.005204857,0.003677803,0.002805715,0.00001679769,0.0001383602,0.00002047326,0.002357348],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003787782,"threshold_uncertainty_score":0.01319885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03113229019833664,"score_gpt":0.2585407715690278,"score_spread":0.2274084813706911,"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."}}