{"id":"W2072653041","doi":"10.1371/journal.pone.0106042","title":"Allelic Combinations of Soybean Maturity Loci E1, E2, E3 and E4 Result in Diversity of Maturity and Adaptation to Different Latitudes","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agriculture and Agri-Food Canada; University of Illinois at Urbana-Champaign; Hokkaido University; Chinese Academy of Sciences; National Natural Science Foundation of China; Chinese Academy of Agricultural Sciences; U.S. Department of Agriculture","keywords":"Biology; photoperiodism; Cultivar; Allele; Genetic diversity; Maturity (psychological); Adaptation (eye); Latitude; Genetics; Gene; Botany; Horticulture; Population; Geography","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":[0.0001456735,0.0003083351,0.0001572526,0.0004379065,0.0001299065,0.0001626319,0.0001639885,0.0001780109,0.0009844674],"category_scores_gemma":[0.0001754762,0.000147751,0.0002823911,0.0002500504,0.0001500589,0.0001108494,0.0002885842,0.0002769626,0.0001558833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001562098,"about_ca_system_score_gemma":0.0000885266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004105416,"about_ca_topic_score_gemma":0.001218635,"domain_scores_codex":[0.9998734,0.00002170706,0.00001471524,0.00004586895,0.00001909121,0.00002523296],"domain_scores_gemma":[0.999866,0.00002794962,0.0000541285,0.00001352494,0.000009035494,0.00002934886],"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":[0.0001959435,0.00002241616,0.01544625,0.00001340887,0.000019499,0.0001342854,0.0000390727,0.00007138455,0.9820107,0.00006857827,0.000012056,0.001966398],"study_design_scores_gemma":[0.00007904632,0.0002793896,0.7580311,0.000009221462,0.0001467088,0.001754987,0.0002227246,0.001748645,0.235616,0.0002828715,0.001802833,0.00002644255],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991077,0.00003727443,0.0005125717,0.000007916668,0.000001279672,0.000003155676,0.0001000331,0.000007546734,0.0002226566],"genre_scores_gemma":[0.998296,0.00003618812,0.0007561596,0.00001633728,0.000001229036,0.000006352514,0.00035526,0.000008982313,0.0005235821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009844674,"threshold_uncertainty_score":0.003293335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05115753992874238,"score_gpt":0.2067132261937114,"score_spread":0.155555686264969,"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."}}