{"id":"W2766338267","doi":"10.1371/journal.pone.0187224","title":"Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Plant Micronutrient Interactions and Effects","field":"Agricultural and Biological Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Plant Sciences Institute, Iowa State University; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Quantitative trait locus; Backcrossing; Biofortification; Introgression; Oryza sativa; Biology; Allele; Plant genetics; Inbred strain; Agronomy; Genetics; Zinc; Genome; Gene; Chemistry","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":[0.0001686222,0.0002537562,0.0002019655,0.0003243935,0.0001359891,0.0001597967,0.0002748223,0.0001785196,0.0004427786],"category_scores_gemma":[0.0001659481,0.000168916,0.0002814713,0.0002875959,0.0001652056,0.0001013555,0.0002682191,0.0003453556,0.0001026857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003245076,"about_ca_system_score_gemma":0.0001866125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004066448,"about_ca_topic_score_gemma":0.00600236,"domain_scores_codex":[0.9998956,0.000009817809,0.000009037226,0.00004838208,0.00002420416,0.00001291577],"domain_scores_gemma":[0.999904,0.00001975186,0.00003297015,0.00001380429,0.00001158356,0.00001782221],"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":[0.00003505054,0.000009515254,0.0009893304,0.00001328947,0.000003069056,0.00002239893,0.00003684907,0.00001910604,0.9980041,0.00001793128,0.000005245409,0.0008439351],"study_design_scores_gemma":[0.00007230462,0.0005167134,0.6178583,0.00001318732,0.0001209356,0.0005844973,0.0002554504,0.003717652,0.3726555,0.0001638782,0.004015093,0.00002650422],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976245,0.00008014974,0.00168746,0.00003348117,0.000003451123,0.00001457087,0.0003185278,0.00003052795,0.0002072605],"genre_scores_gemma":[0.988488,0.0002132387,0.007273144,0.00006114816,0.000002883171,0.00004311075,0.001229233,0.00002848376,0.002660723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004066448,"threshold_uncertainty_score":0.008085549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0755860934389235,"score_gpt":0.2665790228705041,"score_spread":0.1909929294315806,"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."}}