{"id":"W2094838394","doi":"10.2135/cropsci2000.40139x","title":"Developing High‐Protein, High‐Yield Soybean Populations and Lines","year":2000,"lang":"en","type":"article","venue":"Crop Science","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"High protein; Biology; Maple; Cultivar; Yield (engineering); Reciprocal cross; Agronomy; Horticulture; Breeding program; Botany; Food science; Hybrid","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005567486,0.0002773691,0.0002311862,0.000444818,0.0003737705,0.0002517025,0.0005664255,0.0002527621,0.0009850167],"category_scores_gemma":[0.0002781627,0.0002751025,0.0002113692,0.00019911,0.0001495441,0.0001836558,0.0004163768,0.0005263712,0.0005064561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004651131,"about_ca_system_score_gemma":0.0004016249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002678729,"about_ca_topic_score_gemma":0.01248704,"domain_scores_codex":[0.9997452,0.00003663797,0.0000340296,0.00004898478,0.0001110012,0.00002411969],"domain_scores_gemma":[0.9997225,0.00004240048,0.0000523647,0.00004220675,0.00006188366,0.00007871817],"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":[0.0001547417,0.000128152,0.002738388,0.00003842539,0.00001450897,0.0001129037,0.0001358014,0.0002229443,0.9901752,0.0001066491,0.00009940902,0.006072871],"study_design_scores_gemma":[0.0005443479,0.004358127,0.2173996,0.00006403695,0.0001974143,0.002767978,0.0006041694,0.0066792,0.7487909,0.0002274995,0.01827444,0.00009230983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908935,0.0001210702,0.006499934,0.00002997978,0.00001040207,0.0003837482,0.0004234156,0.000106759,0.001531268],"genre_scores_gemma":[0.9293888,0.0005339992,0.05586933,0.0001525203,0.00001279764,0.0008390403,0.004203255,0.0002225137,0.008777723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002678729,"threshold_uncertainty_score":0.005326331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05198514739458943,"score_gpt":0.2522921268078648,"score_spread":0.2003069794132754,"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."}}