{"id":"W2775612564","doi":"10.1007/s00122-017-3036-8","title":"Genetic dissection and validation of candidate genes for flag leaf size in rice (Oryza sativa L.)","year":2017,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"National Natural Science Foundation of China","keywords":"Biology; Quantitative trait locus; Oryza sativa; Leaf size; Candidate gene; Population; Japonica; Genetics; Gene; Horticulture; Botany","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000152997,0.0001282208,0.0001681544,0.00002290079,0.0001795759,0.00004631091,0.0001242585,0.0001175215,0.00001039438],"category_scores_gemma":[0.00006465239,0.0001153202,0.00002879833,0.00001796706,0.0003927925,0.000002058873,0.0001268554,0.0000414172,6.428926e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002451554,"about_ca_system_score_gemma":0.00001549977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001121146,"about_ca_topic_score_gemma":0.000008644161,"domain_scores_codex":[0.9992762,0.00001996493,0.0001745792,0.0002770964,0.00007535679,0.0001768159],"domain_scores_gemma":[0.9995341,0.00004356533,0.00009272542,0.0002217879,0.00003502071,0.00007283205],"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":[0.0004057607,0.00007111115,0.02085742,0.0001644583,0.00003897731,0.000001055417,0.0001753995,0.00009604104,0.9472808,0.01649371,0.00008291673,0.0143324],"study_design_scores_gemma":[0.002165559,0.0005530881,0.191856,0.00003960609,0.000096811,0.00001741257,0.0003188456,0.0005146631,0.7758115,0.02664486,0.001546921,0.0004347902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964272,0.0004255886,0.001403315,0.0001125682,0.00004633417,0.0002245794,0.00004463728,0.000003907599,0.001311913],"genre_scores_gemma":[0.9964964,0.001073637,0.00217677,0.00004138364,0.00009482069,0.00001260411,0.00001683885,0.000009477708,0.00007800835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1714693,"threshold_uncertainty_score":0.4702619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008317371309588971,"score_gpt":0.2381948131690147,"score_spread":0.2298774418594257,"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."}}