{"id":"W2771920161","doi":"10.1111/pbi.12870","title":"Application of protoplast technology to CRISPR/Cas9 mutagenesis: from single‐cell mutation detection to mutant plant regeneration","year":2017,"lang":"en","type":"article","venue":"Plant Biotechnology Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":335,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Agricultural Biotechnology Research Center, Academia Sinica; Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; Chinese Academy of Sciences; Academia Sinica","keywords":"Biology; CRISPR; Mutagenesis; Protoplast; Cas9; Mutant; Genetics; Nicotiana tabacum; DNA; Insertional mutagenesis; Gene; Phytoene desaturase; Transfection; Molecular 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":[0.0003932094,0.0005324351,0.0004207984,0.0005208327,0.0003178889,0.00043997,0.0004713024,0.0005125483,0.001294641],"category_scores_gemma":[0.0002348654,0.0003948708,0.0003794484,0.0002785045,0.0003431034,0.0003243354,0.0005715635,0.001103322,0.0009556231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003631792,"about_ca_system_score_gemma":0.0003346083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004497572,"about_ca_topic_score_gemma":0.0008132275,"domain_scores_codex":[0.9997463,0.00003668902,0.00003155137,0.00008551256,0.00007200653,0.00002792504],"domain_scores_gemma":[0.9997693,0.00005950233,0.00004558627,0.00005710208,0.00002995519,0.00003865261],"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":[0.00001180998,0.000004744702,0.00005314887,0.00002879492,0.00000206169,0.00003405306,0.000009108087,0.00002897817,0.9982004,0.00008044104,0.00003329811,0.001513214],"study_design_scores_gemma":[0.000004512022,0.00005297925,0.0009513202,0.000004611646,0.00001201271,0.0005065955,0.00001029466,0.0008920541,0.9924285,0.00008897096,0.005038532,0.00000954779],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4664622,0.002937968,0.5148909,0.0008711479,0.0003734751,0.0007201262,0.00281723,0.004836228,0.006090798],"genre_scores_gemma":[0.723655,0.003961276,0.2574058,0.00031284,0.0000404631,0.0004154861,0.00430193,0.0005837636,0.009323371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001294641,"threshold_uncertainty_score":0.004330993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007076309430220888,"score_gpt":0.2609948396821039,"score_spread":0.253918530251883,"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."}}