{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001759984,0.0001591653,0.0001500189,0.00003378384,0.00009271775,0.0002425187,0.0001314792,0.00007915819,0.00004599772],"category_scores_gemma":[0.0001007822,0.00007807735,0.00006652655,0.0002170409,0.000009874684,0.0002071468,0.00005826167,0.000112703,0.000003790543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003539295,"about_ca_system_score_gemma":0.000007178699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007156483,"about_ca_topic_score_gemma":0.00006437072,"domain_scores_codex":[0.998865,0.000009798223,0.000249232,0.0003907885,0.000168724,0.000316455],"domain_scores_gemma":[0.999607,0.0002051833,0.00004143474,0.0000314949,0.00003218127,0.00008272233],"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":[0.00001572033,0.0000215085,0.00005080303,0.00004346136,0.00001112287,0.00001482142,0.0001111472,0.00001128878,0.8651738,0.0006851127,0.0001305211,0.1337306],"study_design_scores_gemma":[0.000946411,0.002447298,0.03006724,0.0006096247,0.0000646876,0.00005998186,0.003257188,0.01878983,0.9081985,0.001110933,0.03345164,0.0009966445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954897,0.001101277,0.0002742772,0.001640924,0.0001908981,0.0006117692,0.0001015571,0.00006907037,0.0005205965],"genre_scores_gemma":[0.9986632,0.00007270038,0.000247275,0.0005824034,0.0001187831,0.0001122279,0.00005110803,0.000002688768,0.0001495879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132734,"threshold_uncertainty_score":0.3183902,"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."}}