{"id":"W2953681722","doi":"10.1016/j.molp.2019.06.010","title":"Nanoparticle-Mediated Genetic Engineering of Plants","year":2019,"lang":"en","type":"article","venue":"Molecular Plant","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":112,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of Food and Agriculture; Foundation for Food and Agriculture Research; Innovative Genomics Institute; California Institute for Quantitative Biosciences; Arnold and Mabel Beckman Foundation; Canadian Aeronautics and Space Institute; Burroughs Wellcome Fund; University of California Berkeley; National Institute of General Medical Sciences; Schlumberger Foundation; U.S. Department of Agriculture","keywords":"Biology; Biotechnology; Computational biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001968848,0.0003928429,0.0002731612,0.0002501701,0.0002568913,0.0004869765,0.0003622688,0.0006880039,0.0008359641],"category_scores_gemma":[0.0001961078,0.0002166884,0.0003268683,0.0001417772,0.0002756208,0.0003263231,0.0003473418,0.0006745948,0.0007333013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000536764,"about_ca_system_score_gemma":0.0001794458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004763269,"about_ca_topic_score_gemma":0.001047854,"domain_scores_codex":[0.9997762,0.00002467608,0.00001044864,0.00006659525,0.00008606032,0.00003605594],"domain_scores_gemma":[0.999894,0.00002837862,0.00002184138,0.00001710212,0.0000239007,0.00001475547],"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":[0.00001258483,0.000008512059,0.00001644551,0.0000267982,0.000003207986,0.00002537287,0.00001301887,0.0001236678,0.997964,0.0003299793,0.00005310078,0.00142332],"study_design_scores_gemma":[0.000001915291,0.0000266813,0.00009031093,0.000002547683,0.000005500849,0.00005413106,0.000005290851,0.000881814,0.9963684,0.00006639383,0.002494346,0.000002738796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7698247,0.002832564,0.2030157,0.0005826264,0.0003803675,0.0001773609,0.0004112028,0.001267959,0.02150747],"genre_scores_gemma":[0.9384099,0.0009771163,0.03954776,0.000135694,0.0000198927,0.00008917893,0.000375108,0.0002089549,0.02023641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008359641,"threshold_uncertainty_score":0.003894567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003777340412895083,"score_gpt":0.1780977890269637,"score_spread":0.1743204486140686,"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."}}