{"id":"W3217179662","doi":"10.1007/s13258-021-01187-9","title":"Prospects and challenges of epigenomics in crop improvement","year":2021,"lang":"en","type":"review","venue":"Genes & Genomics","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Biology; Epigenomics; Crop; Human genetics; Biotechnology; Agriculture; Computational biology; Genetics; Agronomy; Ecology; DNA methylation; Gene","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":[0.002147247,0.001085649,0.002039195,0.001891072,0.0002844512,0.001797434,0.001434386,0.002020945,0.006382213],"category_scores_gemma":[0.001917739,0.0003219733,0.0005598165,0.002395782,0.0009398284,0.002684977,0.00137838,0.002350662,0.002596427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008606944,"about_ca_system_score_gemma":0.001543113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001348998,"about_ca_topic_score_gemma":0.002545174,"domain_scores_codex":[0.9996718,0.00008384252,0.0000273938,0.000059542,0.0001133859,0.00004403938],"domain_scores_gemma":[0.9986431,0.0008883537,0.00009345038,0.00003410313,0.0002414918,0.00009939246],"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":[0.0001140944,0.0000566623,0.0001586853,0.01229205,0.00008226158,0.0001625144,0.00004695503,0.0005736259,0.002372456,0.01024867,0.02562644,0.9482656],"study_design_scores_gemma":[0.00002616732,0.00009023039,0.0005507534,0.003658128,0.0001235585,0.0004600594,0.00007543088,0.0001500205,0.000480713,0.005648106,0.9887122,0.000024544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005918921,0.9984024,0.0002696357,0.0004750576,0.0001830532,0.000002105504,0.00001553506,0.000006996566,0.0005859575],"genre_scores_gemma":[0.0004094802,0.9982003,0.0003684498,0.0003835196,0.0002238613,0.000004800883,0.00003229787,0.000001878451,0.0003754523],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006382213,"threshold_uncertainty_score":0.02135068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08056222445512613,"score_gpt":0.2903687108670929,"score_spread":0.2098064864119668,"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."}}