{"id":"W3169425360","doi":"10.3389/fpls.2021.667013","title":"The Cowpea Kinome: Genomic and Transcriptomic Analysis Under Biotic and Abiotic Stresses","year":2021,"lang":"en","type":"article","venue":"Frontiers in Plant Science","topic":"Agricultural pest management studies","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; Université de Sherbrooke","funders":"Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Biology; Gene duplication; Genetics; Kinome; Gene; Synteny; Medicago truncatula; Abiotic stress; Tandem exon duplication; Transcriptome; Vigna; Phylogenetics; Genome; Evolutionary biology; Botany; Gene expression; Symbiosis","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":[0.00009118427,0.0002106787,0.0002535216,0.0006753998,0.0002700381,0.0003277111,0.00009536343,0.000201404,0.0007061125],"category_scores_gemma":[0.0001140696,0.0001025802,0.0002786859,0.0006778655,0.0001142663,0.0002599276,0.0003192946,0.0002303365,0.0001770093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001632051,"about_ca_system_score_gemma":0.0001582734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001147222,"about_ca_topic_score_gemma":0.001434135,"domain_scores_codex":[0.9999188,0.000006152332,0.000003319662,0.00003778452,0.00001205561,0.00002186039],"domain_scores_gemma":[0.9999146,0.00001570801,0.00002442757,0.000008377444,0.00001593828,0.00002080973],"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":[0.0002431079,0.00001152072,0.009395315,0.0001249807,0.000035676,0.0001444424,0.0001885145,0.00008206501,0.9856382,0.00003590887,0.00004424083,0.004056002],"study_design_scores_gemma":[0.000009821951,0.0001647936,0.9267813,0.0000195246,0.0001170267,0.001217916,0.0004653079,0.0008787048,0.06616905,0.0001428643,0.004012799,0.00002093063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949089,0.001302533,0.0008919784,0.0000314058,0.000003869566,0.00001130887,0.002533779,0.00002075193,0.0002955865],"genre_scores_gemma":[0.9841776,0.001262634,0.002938696,0.000074781,0.00001636399,0.00004058694,0.009963548,0.0000225907,0.001503286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001147222,"threshold_uncertainty_score":0.002362132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008948182023097648,"score_gpt":0.1843715750127784,"score_spread":0.1754233929896807,"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."}}