{"id":"W2043675383","doi":"10.1016/j.jgg.2013.03.012","title":"An in vivo Transient Expression System Can Be Applied for Rapid and Effective Selection of Artificial MicroRNA Constructs for Plant Stable Genetic Transformation","year":2013,"lang":"en","type":"article","venue":"Journal of genetics and genomics/Journal of Genetics and Genomics","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Ministry of Education of the People's Republic of China","keywords":"Biology; Transformation (genetics); Transgene; Gene; microRNA; Agrobacterium; Phenotype; Genetically modified crops; Gene expression; Computational biology; Arabidopsis; Genetics; Cell biology; Mutant","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":[0.0006343167,0.0001797289,0.0004712374,0.0001122706,0.0001372082,0.00008350404,0.000157313,0.0001752218,0.000003164084],"category_scores_gemma":[0.00001044947,0.0001005894,0.00008850132,0.00007850464,0.0001091797,0.00004844942,0.00002127939,0.0001581836,3.566358e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006126584,"about_ca_system_score_gemma":0.00009379662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001748697,"about_ca_topic_score_gemma":0.0001310098,"domain_scores_codex":[0.9984506,0.00008540772,0.0008696245,0.0001777874,0.0001448019,0.0002717811],"domain_scores_gemma":[0.9985709,0.0001612697,0.0006457445,0.00004136731,0.0003773548,0.0002034241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006223256,0.00005761436,0.0007473674,0.00009880848,0.00005793667,0.000001892656,0.0006129947,0.0006217356,0.9564924,0.00002909748,0.00002288409,0.04063491],"study_design_scores_gemma":[0.002311869,0.005778119,0.03376205,0.0001061301,0.0001633614,0.000878243,0.002187763,0.01048261,0.9412141,0.0008836983,0.001909674,0.0003223382],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994785,0.002268963,0.001498522,0.000173879,0.0001197804,0.0008809186,0.0002676406,0.000001336529,0.000003946932],"genre_scores_gemma":[0.9873949,0.003409887,0.00893068,0.00003536853,0.0002009496,0.000009982374,0.00001223813,0.00000504494,0.000001003836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04031257,"threshold_uncertainty_score":0.4101916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211637767760166,"score_gpt":0.2118187132307258,"score_spread":0.1997023355531242,"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."}}