{"id":"W3049768643","doi":"10.1111/pbi.13466","title":"Soybean (<i>Glycine max</i>) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics","year":2020,"lang":"en","type":"article","venue":"Plant Biotechnology Journal","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Grain Research Centre; University of Guelph; Université Laval","funders":"Office of Science; Government of Canada; Joint Genome Institute; Grain Farmers of Ontario; Canadian Field Crop Research Alliance; Genome Canada; Syngenta Canada; Saskatchewan Pulse Growers; Génome Québec; U.S. Department of Energy","keywords":"Biology; Haplotype; Genetics; Single-nucleotide polymorphism; Genomics; Gene; Allele; Functional genomics; SNP; Candidate gene; Genome; Computational biology; Genotype","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007902721,0.0005713737,0.0005369441,0.002383852,0.0004916631,0.0005737229,0.0006854338,0.0003214442,0.00787649],"category_scores_gemma":[0.002049992,0.0004395364,0.0003716077,0.00358042,0.0001759072,0.0005852671,0.001250555,0.0006284934,0.003609539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003565394,"about_ca_system_score_gemma":0.001031516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003546326,"about_ca_topic_score_gemma":0.005240149,"domain_scores_codex":[0.9997177,0.00005490814,0.00002665352,0.000115049,0.00005455457,0.00003113502],"domain_scores_gemma":[0.9988548,0.0002465841,0.0003255493,0.0002364707,0.0001226016,0.0002139836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003842498,0.000245572,0.05786988,0.003027544,0.0005727468,0.001848326,0.001587011,0.006968859,0.2801273,0.005978706,0.0812434,0.5566882],"study_design_scores_gemma":[0.0009300999,0.0007940959,0.3618569,0.0005856438,0.000482118,0.002762634,0.0003810028,0.01185833,0.04997914,0.00615319,0.5640153,0.0002014503],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2664519,0.002143951,0.1560084,0.0006121158,0.0002118697,0.000607237,0.5468416,0.01420598,0.01291695],"genre_scores_gemma":[0.153567,0.0006396099,0.1709485,0.0001144806,0.00009520516,0.0005981507,0.6698949,0.00174023,0.002401901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00787649,"threshold_uncertainty_score":0.02634948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254901622094978,"score_gpt":0.186382113253282,"score_spread":0.1608919510437842,"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."}}