{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006053829,0.0006828479,0.0009840463,0.0003284635,0.0001038655,0.0001769381,0.0005313479,0.0008708187,0.00004592093],"category_scores_gemma":[0.0001559782,0.0005457841,0.0005275395,0.0002141164,0.0003397327,0.000003823465,0.0009035173,0.0006517572,0.0002120548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008340216,"about_ca_system_score_gemma":0.0007266039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001042393,"about_ca_topic_score_gemma":0.000005991104,"domain_scores_codex":[0.9967479,0.0001185658,0.0008076495,0.0009040802,0.0006990213,0.0007228035],"domain_scores_gemma":[0.9985697,0.00002959734,0.000186972,0.0006133289,0.00008565292,0.0005148104],"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":[0.0000295459,0.00007969527,0.00000169095,0.01693928,0.001697266,0.0007480219,0.00005149255,0.000002284591,0.01375749,0.0005318878,0.03614222,0.9300191],"study_design_scores_gemma":[0.0002146304,0.0002309435,6.488493e-7,0.001312492,0.000666078,0.0005626798,0.00002306108,0.00007075705,0.0009245513,0.0001059592,0.9952798,0.0006084081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001517728,0.9948395,0.001939614,0.000136267,0.0006157208,0.0006289213,0.0005643947,0.00003530091,0.001088445],"genre_scores_gemma":[0.00009672693,0.9933249,0.0007825064,0.0003543648,0.0005317507,0.0000809568,0.004029489,0.0001236533,0.0006755912],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9591376,"threshold_uncertainty_score":0.9996994,"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."}}