{"id":"W2914575671","doi":"10.1111/pbr.12679","title":"Density enhancement of a faba bean genetic linkage map (<i>Vicia faba</i>) based on simple sequence repeats markers","year":2019,"lang":"en","type":"article","venue":"Plant Breeding","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture Food and Rural Development; University of Alberta","funders":"Agriculture Research System of China; Chinese Academy of Agricultural Sciences; National Natural Science Foundation of China","keywords":"Vicia faba; Biology; Genetic linkage; Genetics; Genetic marker; Linkage (software); Microsatellite; Gene mapping; Genetic linkage map; Allele; Botany; Gene; Chromosome","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":[0.0003568395,0.0004535122,0.0003845031,0.000940925,0.0002120679,0.0002327181,0.0004026679,0.0001581476,0.00113776],"category_scores_gemma":[0.0003719316,0.0003188535,0.0005368307,0.0004687101,0.0001361167,0.0001855584,0.0004903231,0.000482486,0.000372597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006964633,"about_ca_system_score_gemma":0.000484284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005822954,"about_ca_topic_score_gemma":0.0103769,"domain_scores_codex":[0.9997421,0.00004150434,0.00001309629,0.00008602728,0.00006571616,0.00005155042],"domain_scores_gemma":[0.9998031,0.00003609919,0.00005041551,0.0000169979,0.00004522299,0.00004822574],"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":[0.0000915598,0.00004645361,0.002427652,0.00004536275,0.00002489192,0.00008289934,0.00004188676,0.0003759867,0.9858006,0.0001173237,0.00007697185,0.01086842],"study_design_scores_gemma":[0.0002537064,0.001326095,0.4525694,0.0001005903,0.0006071846,0.002017023,0.0002028779,0.01732472,0.5038591,0.0005503859,0.02110727,0.00008173659],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9275652,0.0008225466,0.06690978,0.00008515418,0.00002699404,0.0002434125,0.001018671,0.0006334647,0.002694803],"genre_scores_gemma":[0.8878771,0.0005588185,0.1027922,0.00005752938,0.00001410992,0.0001561956,0.005300504,0.000101104,0.003142453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005822954,"threshold_uncertainty_score":0.01157814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02368384167862754,"score_gpt":0.197403469076658,"score_spread":0.1737196273980304,"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."}}