{"id":"W4387378230","doi":"10.1016/j.xplc.2023.100725","title":"A Brassica carinata pan-genome platform for Brassica crop improvement","year":2023,"lang":"en","type":"article","venue":"Plant Communications","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Biotechnology and Biological Sciences Research Council; National Natural Science Foundation of China; National University's Basic Research Foundation of China; Directorate for Biological Sciences; Fundamental Research Funds for the Central Universities; Huazhong Agricultural University; Grains Research and Development Corporation","keywords":"Brassica carinata; Brassica; Biology; Crop; Genome; Agronomy; Gene; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005911083,0.001065339,0.0008408646,0.000873446,0.0008298501,0.0006851063,0.0009871281,0.0007883124,0.01040749],"category_scores_gemma":[0.0003618137,0.000804402,0.000778882,0.0007957171,0.0002221442,0.0004298878,0.001093809,0.00180093,0.008362597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005276861,"about_ca_system_score_gemma":0.0008094835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002959259,"about_ca_topic_score_gemma":0.00702133,"domain_scores_codex":[0.9995957,0.00004508513,0.00001981823,0.0001408323,0.0001357065,0.00006283542],"domain_scores_gemma":[0.9997118,0.00004053571,0.00004249293,0.00006814321,0.00004920019,0.00008770998],"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":[0.0003236338,0.00005885058,0.0002141424,0.000175271,0.00002655965,0.00008397171,0.00006115887,0.0002288194,0.9745834,0.000598123,0.00577514,0.0178709],"study_design_scores_gemma":[0.0004552229,0.0005709198,0.00873396,0.0001284869,0.000278747,0.00077911,0.0001014241,0.00577048,0.6053945,0.001078004,0.3765982,0.0001110199],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2636242,0.006501499,0.4278446,0.001891151,0.001661298,0.004535433,0.1265578,0.09236788,0.07501613],"genre_scores_gemma":[0.301223,0.005230448,0.3272426,0.00142275,0.0001670761,0.003117045,0.2460676,0.01315512,0.1023743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01040749,"threshold_uncertainty_score":0.0348165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04265481201183389,"score_gpt":0.2868675617299304,"score_spread":0.2442127497180966,"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."}}