{"id":"W2550424410","doi":"10.1007/s00122-016-2819-7","title":"Mapping and identification of a potential candidate gene for a novel maturity locus, E10, in soybean","year":2016,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":174,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Carleton University; Agriculture and Agri-Food Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Field Crop Research Alliance","keywords":"Biology; Plant biochemistry; Locus (genetics); Identification (biology); Genetics; Gene; Computational biology; Gene mapping; Biotechnology; Maturity (psychological); Candidate gene; Botany","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":[0.0002079606,0.00008699531,0.0001231704,0.00001223494,0.00005515959,0.00002133668,0.00007114221,0.00007311192,0.00001864357],"category_scores_gemma":[0.00001641002,0.00003393964,0.00002124226,0.00008459762,0.0002355049,0.00001199628,0.0000510562,0.00002884364,7.557908e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005117543,"about_ca_system_score_gemma":0.00000320129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004682906,"about_ca_topic_score_gemma":0.000009263955,"domain_scores_codex":[0.9993018,0.00001204407,0.0002293507,0.0002138992,0.00008818245,0.000154746],"domain_scores_gemma":[0.9997237,0.00008028992,0.00006540893,0.00004212678,0.00003342249,0.00005505086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004903168,0.00003550072,0.0004308939,0.00001020371,0.000004034237,7.344447e-8,0.00006298161,0.00000128445,0.8935359,0.04980883,0.000004325699,0.05605699],"study_design_scores_gemma":[0.00117287,0.0001679436,0.1940469,0.00003762809,0.00002302692,0.000005244695,0.0003362033,0.001118141,0.6028733,0.1996399,0.0002888153,0.0002899793],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950708,0.00009800965,0.003784719,0.0006174528,0.00002180994,0.0002587727,0.00008676611,0.000008343249,0.00005331105],"genre_scores_gemma":[0.9989905,0.0001297452,0.0007154068,0.00004156437,0.00006789741,0.00001968052,0.00001789532,0.000001308387,0.00001597429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2906625,"threshold_uncertainty_score":0.1384018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009520771675868492,"score_gpt":0.2051598544594817,"score_spread":0.1956390827836132,"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."}}