{"id":"W4401276537","doi":"10.5376/mpb.2024.15.0009","title":"Precision Editing: Revolutionary Applications of Genome Editing Technology in Tree Breeding","year":2024,"lang":"en","type":"article","venue":"Molecular Plant Breeding","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biology; Genome editing; Genome; Tree (set theory); Computational biology; Evolutionary biology; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001146675,0.0005394575,0.0006635025,0.0006514467,0.0004723954,0.001791112,0.0006661155,0.0009324126,0.001445189],"category_scores_gemma":[0.0007502714,0.0002951532,0.0005173531,0.0005796507,0.000989189,0.001478907,0.001122301,0.001865081,0.000563253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006266909,"about_ca_system_score_gemma":0.0006001527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005084513,"about_ca_topic_score_gemma":0.0006619529,"domain_scores_codex":[0.9993014,0.00010833,0.00003169883,0.0002119683,0.0002643334,0.00008221674],"domain_scores_gemma":[0.9996595,0.0001227868,0.00007959884,0.00005993745,0.0000404709,0.00003758983],"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":[0.0001277789,0.00004587882,0.0007395702,0.0007086392,0.00005126178,0.0004429821,0.0002710443,0.002282456,0.7650167,0.03520086,0.002329004,0.1927839],"study_design_scores_gemma":[0.00003093891,0.0006632521,0.002488671,0.0002523404,0.0001359486,0.003797629,0.0002017866,0.008463488,0.6993408,0.02064013,0.2638307,0.0001543028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1122449,0.1148146,0.7263289,0.005642877,0.001440566,0.0002386112,0.0006749438,0.0030864,0.03552813],"genre_scores_gemma":[0.5809953,0.1270173,0.2726966,0.00203158,0.0007111326,0.0001404808,0.0008777037,0.000465408,0.01506437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001791112,"threshold_uncertainty_score":0.006064236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007137282447151604,"score_gpt":0.2559716509757701,"score_spread":0.2488343685286185,"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."}}