{"id":"W4402072935","doi":"10.5376/lgg.2024.15.0020","title":"CRISPR/Cas9 Genome Editing in Legumes: Opportunities for Functional Genomics and Breeding","year":2024,"lang":"en","type":"article","venue":"Legume Genomics and Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Genome editing; Genomics; Functional genomics; Biology; Genome; Computational 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":[0.001164917,0.0005475669,0.0006123821,0.0005205369,0.0004611891,0.001726397,0.000844838,0.001162543,0.002712499],"category_scores_gemma":[0.0006806913,0.0002914884,0.0007709383,0.0003955441,0.0007478388,0.001198578,0.000925641,0.001675542,0.0006613753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083566,"about_ca_system_score_gemma":0.0009957934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00130571,"about_ca_topic_score_gemma":0.002428937,"domain_scores_codex":[0.9995548,0.00008374266,0.00003048086,0.0001094478,0.0001379127,0.00008361474],"domain_scores_gemma":[0.9996201,0.000121508,0.00007586706,0.00004742964,0.00005223992,0.0000828048],"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":[0.0003097529,0.0001192732,0.001179563,0.0008308043,0.00008464976,0.0006112819,0.0002593887,0.00371349,0.6982545,0.04247757,0.005746248,0.2464135],"study_design_scores_gemma":[0.0001094133,0.001329939,0.005248997,0.0005322627,0.0001942512,0.002130792,0.0005302296,0.01639759,0.4186006,0.03604522,0.5186589,0.0002217097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2239768,0.1188923,0.572759,0.02637038,0.00226237,0.0004807134,0.002241768,0.004607276,0.04840936],"genre_scores_gemma":[0.567735,0.09566914,0.3070198,0.004791987,0.0006105471,0.0002469512,0.002608923,0.0004972118,0.02082038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002712499,"threshold_uncertainty_score":0.009074152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02847308651354584,"score_gpt":0.2777563198513749,"score_spread":0.249283233337829,"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."}}