{"id":"W3109534956","doi":"10.3390/genes11111387","title":"GWAS Based on RNA-Seq SNPs and High-Throughput Phenotyping Combined with Climatic Data Highlights the Reservoir of Valuable Genetic Diversity in Regional Tomato Landraces","year":2020,"lang":"en","type":"article","venue":"Genes","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"European Social Fund; Università degli Studi di Sassari; National Science Foundation","keywords":"Biology; Genome-wide association study; Quantitative trait locus; Context (archaeology); Single-nucleotide polymorphism; Genetic diversity; Genetics; Candidate gene; Genomics; Genetic variation; Genetic architecture; Association mapping; Genome; Phenotypic trait; Computational biology; Evolutionary biology; Phenotype; Gene; Genotype; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006164032,0.0002917231,0.0004610968,0.0007908119,0.0003062618,0.0004309605,0.0002092892,0.0002110416,0.001159135],"category_scores_gemma":[0.0003983892,0.0001311756,0.0004084553,0.0007896011,0.0002958138,0.00021361,0.0004105619,0.0002484406,0.0002466276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002242303,"about_ca_system_score_gemma":0.0001549936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001316746,"about_ca_topic_score_gemma":0.004520206,"domain_scores_codex":[0.9995533,0.00008586777,0.00003725423,0.0002088162,0.00007979254,0.00003484897],"domain_scores_gemma":[0.9994764,0.0001743056,0.0001483453,0.0001067594,0.00004160485,0.00005268879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002080802,0.00005013842,0.1036112,0.00006911122,0.0002176693,0.0002022146,0.0001578365,0.0004817398,0.8878918,0.0001265752,0.00007358324,0.006910022],"study_design_scores_gemma":[0.00001294662,0.0001317751,0.9759256,0.000008528346,0.0001113798,0.0003076906,0.0001107008,0.001265942,0.02056611,0.0001652934,0.001380872,0.00001331979],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942386,0.0001738465,0.00374957,0.00002709447,0.000003361057,0.0000126633,0.001312948,0.00005334173,0.0004285497],"genre_scores_gemma":[0.9929475,0.0001000955,0.003526179,0.00006212567,0.000008011245,0.0000304216,0.002846207,0.0000394219,0.0004399616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001316746,"threshold_uncertainty_score":0.003877699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05274733689071046,"score_gpt":0.247397063291894,"score_spread":0.1946497264011836,"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."}}