{"id":"W4405904975","doi":"10.1016/j.molp.2024.12.015","title":"Medicago2035: Genomes, functional genomics, and molecular breeding","year":2024,"lang":"en","type":"review","venue":"Molecular Plant","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biotechnology Research Institute","funders":"National Key Research and Development Program of China; China Academy of Space Technology; National Natural Science Foundation of China; U.S. Department of Agriculture; National Institute of Food and Agriculture; National Science Foundation","keywords":"Biology; Genomics; Genome; Functional genomics; Computational biology; Evolutionary biology; Molecular breeding; Genetics; Gene","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":[0.0006509679,0.001228014,0.001317053,0.001823642,0.0002191798,0.001133812,0.001363922,0.001384554,0.00507488],"category_scores_gemma":[0.0007221905,0.0003668488,0.0003605928,0.002960166,0.0005887159,0.001309528,0.00103541,0.002105612,0.003823033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009810649,"about_ca_system_score_gemma":0.001201539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001386008,"about_ca_topic_score_gemma":0.002626579,"domain_scores_codex":[0.999836,0.00002193873,0.00001669791,0.00003491645,0.00006926406,0.00002125179],"domain_scores_gemma":[0.9996833,0.000128948,0.00005203508,0.00001510812,0.00007309933,0.00004758633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001337842,0.00004370875,0.00007671228,0.01169874,0.00006281438,0.000123356,0.00002767677,0.0003207082,0.004699661,0.005392082,0.06465622,0.9127646],"study_design_scores_gemma":[0.00001516553,0.00003126979,0.0003210236,0.001129474,0.00005989254,0.0003227974,0.00001100778,0.00003564192,0.0005137502,0.001202681,0.9963484,0.000008855407],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001051046,0.9974119,0.0003218843,0.0005453765,0.0002569932,0.000005591897,0.00007053834,0.00003302649,0.001249499],"genre_scores_gemma":[0.0006974545,0.9965663,0.0005168963,0.000593767,0.0002026396,0.00001010878,0.0002252154,0.000005930284,0.001181677],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00507488,"threshold_uncertainty_score":0.01697719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116923273709466,"score_gpt":0.2900178162610552,"score_spread":0.2588485835239606,"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."}}