{"id":"W3042186428","doi":"10.1021/acs.jafc.0c02053","title":"Metabolomic Analyses Provide New Insights into Signaling Mechanisms for Nutrient Uptake by Lateral Roots of Pruned Tea Plant (<i>Camellia sinensis</i>)","year":2020,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Tea Polyphenols and Effects","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Science Foundation of Jiangsu Province; China Postdoctoral Science Foundation; Ministry of Education of the People's Republic of China","keywords":"Phenylpropanoid; Metabolic pathway; KEGG; Metabolism; Camellia sinensis; Biosynthesis; Biology; Biochemistry; Metabolomics; Flavonoid biosynthesis; Nutrient; Citric acid cycle; Amino acid; Metabolome; Botany; Transcriptome; Gene; Gene expression","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":[0.00005875116,0.0002164768,0.0006379168,0.00001898836,0.00005213113,0.00002867269,0.00009520999,0.0001172404,0.00001065088],"category_scores_gemma":[0.00006850259,0.0001147455,0.0002454345,0.0001269336,0.00002494702,0.0001096889,0.00002992714,0.0002109864,3.380455e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002743364,"about_ca_system_score_gemma":0.00006192904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001038668,"about_ca_topic_score_gemma":9.729523e-7,"domain_scores_codex":[0.9988034,0.00001198513,0.0005628634,0.0001812927,0.0002567897,0.0001836958],"domain_scores_gemma":[0.9988611,0.00004488787,0.0004752529,0.00006240212,0.0001695789,0.0003867636],"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":[0.0005289295,0.00008896836,0.00003657245,0.0005023499,0.0004174183,0.000007963288,0.0005769948,0.00002282247,0.9934044,0.00001351701,0.004042184,0.0003578826],"study_design_scores_gemma":[0.002530011,0.001304635,0.001580231,0.0002340648,0.0006163894,0.0001481727,0.0005432112,0.00004867005,0.9913558,0.0002559309,0.00122709,0.0001558458],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917816,0.005245037,0.0003919151,0.002263728,0.00005995324,0.0002051547,0.00002349728,0.00001368792,0.00001543417],"genre_scores_gemma":[0.9970006,0.0001139229,0.002064997,0.0001893523,0.0004792434,0.000002762089,0.00004449415,0.00001042507,0.00009416799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005219042,"threshold_uncertainty_score":0.4679187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950131157648085,"score_gpt":0.23853061091132,"score_spread":0.2190292993348392,"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."}}