{"id":"W3129250973","doi":"10.1016/j.cell.2021.01.005","title":"Genome engineering for crop improvement and future agriculture","year":2021,"lang":"en","type":"review","venue":"Cell","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":966,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"National Key Research and Development Program of China; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Biology; Crop; Agriculture; Genome; Biotechnology; Computational biology; Genetics; Agronomy; Gene; Ecology","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":[0.0009197526,0.001792269,0.001908399,0.002204031,0.0002727055,0.0015056,0.001506867,0.00184526,0.005472907],"category_scores_gemma":[0.0008914856,0.000482852,0.0004707113,0.002771696,0.000747677,0.0018495,0.001256692,0.002740925,0.003990511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063291,"about_ca_system_score_gemma":0.001314118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001288337,"about_ca_topic_score_gemma":0.002882515,"domain_scores_codex":[0.9996756,0.00004924741,0.00002852794,0.00005148195,0.0001528617,0.00004226849],"domain_scores_gemma":[0.9996719,0.0001412142,0.00004595046,0.00001527176,0.00008256606,0.00004306071],"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":[0.0000778208,0.00006136156,0.00004364901,0.01087939,0.00005505201,0.0001233015,0.0000249039,0.0005265598,0.005275415,0.006271357,0.07237472,0.9042864],"study_design_scores_gemma":[0.00001392975,0.00003216949,0.0001337872,0.001170127,0.00004146352,0.0002367872,0.00001217137,0.00008127762,0.0005473092,0.002027273,0.9956929,0.00001076063],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005780552,0.9960012,0.0007385486,0.0004191842,0.0007407932,0.000007547027,0.00003696489,0.00002777828,0.001970127],"genre_scores_gemma":[0.0004103748,0.9963996,0.0006490862,0.0003414991,0.0003467349,0.00001007977,0.00007357955,0.00000633241,0.001762717],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005472907,"threshold_uncertainty_score":0.0183087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006247817933106763,"score_gpt":0.2644955344608631,"score_spread":0.2582477165277564,"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."}}