{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002931691,0.0001202595,0.0001879181,0.00004057751,0.0006792278,0.000256282,0.0002770853,0.00002903176,0.000008471848],"category_scores_gemma":[0.00003730493,0.00003945071,0.00003323543,0.001465142,0.0006793167,0.0001706868,0.000160904,0.00008102002,0.000001503255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004293347,"about_ca_system_score_gemma":0.00001097674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001102089,"about_ca_topic_score_gemma":0.00221668,"domain_scores_codex":[0.9988334,0.00004456312,0.0001602955,0.0004218336,0.0002110208,0.0003288859],"domain_scores_gemma":[0.9996646,0.0001249303,0.00005046229,0.00005904855,0.0000311008,0.00006986957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002751386,0.00006229195,0.8839898,0.00002065469,0.0002239787,0.00003704068,0.000590968,0.0001479498,0.08543593,0.001457085,0.003462514,0.02454435],"study_design_scores_gemma":[0.00006703919,0.00002085853,0.9935695,0.000009004038,0.00007585157,0.000005986638,0.003094064,0.0008289135,0.0003527622,0.0004481063,0.001400495,0.000127412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922058,0.003639331,0.00002249257,0.003623289,0.0002191429,0.0001092315,0.00003221516,0.00001762033,0.000130908],"genre_scores_gemma":[0.9971198,0.002242667,0.0001773327,0.0001470735,0.00002352501,0.000003102261,0.00001341656,3.70221e-7,0.0002726891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1095798,"threshold_uncertainty_score":0.522414,"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."}}