{"id":"W3110781099","doi":"10.20944/preprints202012.0372.v1","title":"Recent Advances in Faba Bean Genetic and Genomic Tools for Crop Improvement","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Directorate for Biological Sciences; Innovationsfonden; Grains Research and Development Corporation; Biotechnology and Biological Sciences Research Council; Saskatchewan Pulse Growers; Academy of Finland; Western Grains Research Foundation","keywords":"Vicia faba; Biology; Agronomy; Biotechnology; Plant breeding; Synteny; Legume; Molecular breeding; Crop; Reference genome; Livestock; Genomics; Genome; Gene; Genetics; Ecology","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":[0.0001593475,0.0002887231,0.0003571404,0.0000103562,0.0001220093,0.00003928799,0.0003305017,0.0001382675,0.0003048401],"category_scores_gemma":[0.00006623513,0.0001422925,0.00009975649,0.00005451615,0.0001022337,0.00005380145,0.001866603,0.0002294906,0.00007508171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009003079,"about_ca_system_score_gemma":0.000009067149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000974228,"about_ca_topic_score_gemma":0.0002974869,"domain_scores_codex":[0.9981856,0.00003815185,0.0003853484,0.0009101996,0.0001504559,0.0003302862],"domain_scores_gemma":[0.9995056,0.00007578421,0.0001550822,0.0001312839,0.00001957701,0.0001126866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006525325,0.0000847643,0.360253,0.00009726844,0.00003449995,0.000002909469,0.0002890131,0.0002225365,0.2131638,0.000009485609,0.00002229,0.4257552],"study_design_scores_gemma":[0.0001887969,0.0001277335,0.9147864,0.00003274894,0.0000235628,9.381217e-7,0.0004076295,0.00003240006,0.006878871,0.001619637,0.07560259,0.0002986922],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871938,0.008861917,0.000009612212,0.001875834,0.0001956195,0.001183599,0.00009740124,0.00003342819,0.0005487601],"genre_scores_gemma":[0.9560516,0.04269468,0.0002749437,0.0002596964,0.0001715417,0.0003713116,0.0000685754,0.000003225565,0.000104465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5545334,"threshold_uncertainty_score":0.5802521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1090973869481037,"score_gpt":0.2889314763409674,"score_spread":0.1798340893928637,"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."}}