{"id":"W4395098342","doi":"10.5376/rgg.2024.15.0002","title":"Development of CRISPR-Cas9 Multiple Editing System for Genetic Improvement of Rice","year":2024,"lang":"en","type":"article","venue":"Rice Genomics and Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Genome editing; Biology; Cas9; Biotechnology; Computer science; 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":[0.000529061,0.0006908548,0.0007901863,0.0006469933,0.0004138486,0.0007131766,0.0006469754,0.000607327,0.001354346],"category_scores_gemma":[0.0003255755,0.0003708125,0.0008246641,0.0005192101,0.0002993414,0.0006712877,0.0005981064,0.001372975,0.0009450989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005552497,"about_ca_system_score_gemma":0.0007609069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001073202,"about_ca_topic_score_gemma":0.001100348,"domain_scores_codex":[0.9996039,0.00003723921,0.00006080077,0.0001135245,0.000137722,0.0000468002],"domain_scores_gemma":[0.9999084,0.00001591037,0.00002047004,0.00001176645,0.00002810999,0.00001525771],"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":[0.00008668518,0.0000359736,0.000496029,0.001440323,0.00005007804,0.0005843078,0.0001152847,0.001151854,0.9131662,0.0037368,0.002214155,0.07692225],"study_design_scores_gemma":[0.00005100197,0.0005682136,0.003055594,0.0001866717,0.0002003742,0.003722637,0.00007075806,0.008120262,0.7797772,0.001702733,0.2024196,0.0001248416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1664208,0.09129739,0.6865937,0.002776739,0.001998665,0.001188855,0.002741775,0.007678898,0.03930334],"genre_scores_gemma":[0.4712783,0.08243056,0.4134319,0.001226184,0.0002532208,0.0005564442,0.004473156,0.0006257833,0.02572461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001354346,"threshold_uncertainty_score":0.004530728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008572562073447771,"score_gpt":0.2623255049025626,"score_spread":0.2537529428291149,"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."}}