{"id":"W4413815779","doi":"10.1002/csc2.70138","title":"Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests","year":2025,"lang":"en","type":"article","venue":"Crop Science","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"North Central Soybean Research Program; National Science Foundation","keywords":"Biology; Computational biology; Evolutionary biology; Genetics; Genomic selection; Gene; Genotype","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":[0.0004053157,0.000048906,0.00005732452,0.000037042,0.000294464,0.000117243,0.0002911748,0.00001874154,0.000005687493],"category_scores_gemma":[0.00004455356,0.00001572874,0.00002209503,0.002021842,0.0001565726,0.00006947463,0.00006046139,0.00004711351,0.000001454765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002335849,"about_ca_system_score_gemma":0.00001747885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002564101,"about_ca_topic_score_gemma":0.002905602,"domain_scores_codex":[0.9994159,0.00001622091,0.00009160594,0.0002045931,0.0001342779,0.0001374495],"domain_scores_gemma":[0.9998034,0.00004500642,0.00002243313,0.0000495411,0.00005738249,0.00002220934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007680381,0.00004108547,0.7636986,0.000001802706,0.00001321011,8.537486e-7,0.001305236,0.005893792,0.1758039,0.0004865155,0.000005843808,0.05274155],"study_design_scores_gemma":[0.00002721599,0.00002187023,0.861924,0.000003591841,0.00001458067,2.547748e-7,0.001121143,0.1354241,0.0002816328,0.001110517,0.00003142772,0.00003966961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980868,0.00006254885,0.0002277896,0.0004684047,0.00001952184,0.00008713669,0.000003952885,0.000006983912,0.001036901],"genre_scores_gemma":[0.9997361,0.000009752272,0.0000447293,0.0001512435,0.00001566981,0.000004845033,0.000003916087,1.276702e-7,0.00003365988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1755222,"threshold_uncertainty_score":0.2264809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02012022458176061,"score_gpt":0.2347484433138496,"score_spread":0.214628218732089,"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."}}