{"id":"W4321374324","doi":"10.3390/ijms24044073","title":"Identification of a Rice Leaf Width Gene Narrow Leaf 22 (NAL22) through Genome-Wide Association Study and Gene Editing Technology","year":2023,"lang":"en","type":"article","venue":"International Journal of Molecular Sciences","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chinese Academy of Agricultural Sciences; Chinese Academy of Sciences; Institute of Genetics; National Natural Science Foundation of China; Ohio State University","keywords":"Biology; Gene; Genetics; Genome-wide association study; Genome; Phenotype; Genetic architecture; Candidate gene; CRISPR; Gene expression; Genotype; Single-nucleotide polymorphism","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004048779,0.0003750426,0.0003569752,0.0006178254,0.0002043956,0.0003532348,0.0003265198,0.0002754361,0.00117317],"category_scores_gemma":[0.0002351858,0.0001869841,0.0004755738,0.0004746857,0.0002112802,0.0001070688,0.0004051713,0.0005728645,0.0002472378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001769512,"about_ca_system_score_gemma":0.0002869933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005805,"about_ca_topic_score_gemma":0.002073977,"domain_scores_codex":[0.9998118,0.0000215493,0.00001684304,0.00008114307,0.00004760661,0.00002120131],"domain_scores_gemma":[0.9998165,0.00004226155,0.00006445093,0.00001949814,0.00002115157,0.00003624612],"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":[0.000452016,0.00008714952,0.02891885,0.0002084912,0.0002224257,0.001028758,0.0001629294,0.0005481784,0.9408027,0.0009569312,0.0003876633,0.026224],"study_design_scores_gemma":[0.000342414,0.0006596813,0.6141321,0.00009390149,0.001328565,0.005473521,0.0003816308,0.01881996,0.3155461,0.001630219,0.04146547,0.0001264113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620584,0.001440117,0.0329778,0.0002599031,0.00006399821,0.00005438009,0.001656114,0.0001781387,0.001311115],"genre_scores_gemma":[0.9753656,0.001030584,0.01741205,0.0001854417,0.00002798074,0.00007159456,0.002961142,0.00006948719,0.002876098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00117317,"threshold_uncertainty_score":0.003924668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386880292872876,"score_gpt":0.2704708491813055,"score_spread":0.2566020462525768,"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."}}