{"id":"W4402072619","doi":"10.5376/mpb.2024.15.0018","title":"Advanced Genetic Tools for Rice Breeding: CRISPR/Cas9 and Its Role in Yield Trait Improvement","year":2024,"lang":"en","type":"article","venue":"Molecular Plant Breeding","topic":"Rice Cultivation and Yield Improvement","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fujian Agriculture and Forestry University","keywords":"CRISPR; Biology; Trait; Biotechnology; Yield (engineering); Genetics; Genome editing; Cas9; Quantitative trait locus; Selective breeding; Computational biology; Gene; Computer science","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":[0.0007873083,0.0004396797,0.000410488,0.0006735839,0.0003126313,0.0009189476,0.0006310061,0.0009392675,0.002289028],"category_scores_gemma":[0.0005900661,0.0002466506,0.0004300823,0.000509541,0.0007017473,0.001023218,0.0008080567,0.001580356,0.001132504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006631125,"about_ca_system_score_gemma":0.0005507347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001182005,"about_ca_topic_score_gemma":0.001207497,"domain_scores_codex":[0.9995122,0.00006959256,0.00003103294,0.0001291091,0.0002125641,0.00004552603],"domain_scores_gemma":[0.9997892,0.00005110627,0.00004612072,0.00002460897,0.00004961904,0.00003939162],"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":[0.0002321433,0.00008128073,0.0008086666,0.0008207387,0.00005256097,0.0004957293,0.0001587953,0.002652208,0.7146732,0.02518144,0.00699602,0.2478471],"study_design_scores_gemma":[0.00009304074,0.0008048969,0.004169787,0.0003644204,0.0001238431,0.002396642,0.000188372,0.01708024,0.4663478,0.02412799,0.4841358,0.0001671569],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1523841,0.155033,0.6132416,0.0145639,0.002162166,0.0003397656,0.001971472,0.007102127,0.05320188],"genre_scores_gemma":[0.5061958,0.1106259,0.3410537,0.003811434,0.0007131022,0.00023103,0.002045586,0.0005606253,0.03476298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002289028,"threshold_uncertainty_score":0.007657588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0352261280661836,"score_gpt":0.236582355501276,"score_spread":0.2013562274350924,"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."}}