{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001497806,0.0001443678,0.0001592725,0.00002917052,0.0003898843,0.00005496676,0.0001621922,0.0002506498,0.0001290938],"category_scores_gemma":[0.00003438176,0.00007174449,0.00007459324,0.0001427246,0.0001054598,0.00006223608,0.00004016022,0.0003041077,0.00001039424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001916441,"about_ca_system_score_gemma":0.00002076663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003871594,"about_ca_topic_score_gemma":0.00002510578,"domain_scores_codex":[0.9990873,0.00002643055,0.000230256,0.0002639835,0.0001426976,0.0002492791],"domain_scores_gemma":[0.9995503,0.000102534,0.0001259747,0.00003100046,0.00005241854,0.0001378077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009591216,0.00008768552,0.003982767,0.00001668569,0.0001282967,0.00002623575,0.000303829,0.0000612661,0.9149047,0.01008123,0.01390901,0.05553916],"study_design_scores_gemma":[0.002669185,0.001978419,0.03728412,0.00004020702,0.0001193741,0.0008495341,0.002338958,0.00796771,0.02809034,0.01024607,0.9076849,0.000731191],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9143946,0.0006873524,0.002531704,0.08142632,0.0001576627,0.0002524779,0.0003332093,0.0001203134,0.00009636519],"genre_scores_gemma":[0.9948863,0.0001483134,0.002173425,0.001375529,0.0009270224,0.000004781454,0.0003894244,0.000004125649,0.00009102238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8937759,"threshold_uncertainty_score":0.2998714,"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."}}