{"id":"W2534176501","doi":"10.1126/scisignal.aaf2768","title":"Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the <i>Arabidopsis thaliana</i> root","year":2016,"lang":"en","type":"article","venue":"Science Signaling","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Biological Infrastructure; Division of Molecular and Cellular Biosciences; National Institute of General Medical Sciences; Centre National de la Recherche Scientifique; York University; National Science Foundation; National Institutes of Health; Agence Nationale de la Recherche","keywords":"Arabidopsis thaliana; Transcriptome; Arabidopsis; Biology; Hormone; Phenotype; Nutrient; Plant hormone; Computational biology; Botany; Cell biology; Gene; Genetics; Biochemistry; Ecology; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001410453,0.0001620874,0.0002208869,0.0003045607,0.0001375081,0.000328069,0.0001634667,0.000145482,0.0007145478],"category_scores_gemma":[0.0003761756,0.0001598154,0.000257511,0.0003219288,0.0001961963,0.0002699369,0.0001335642,0.0001867366,0.0001044349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004132771,"about_ca_system_score_gemma":0.0002539757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002911017,"about_ca_topic_score_gemma":0.004199066,"domain_scores_codex":[0.99989,0.00002150502,0.000003772443,0.00005563266,0.0000142318,0.00001482902],"domain_scores_gemma":[0.9997907,0.00008193803,0.00007235262,0.0000134719,0.00002056276,0.00002095055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006200823,0.0001201967,0.08625188,0.0001875718,0.000295839,0.0006573669,0.0001739427,0.1449488,0.7318497,0.006858333,0.0009765037,0.02705972],"study_design_scores_gemma":[0.00002596389,0.000187358,0.3226258,0.00001068036,0.0001649155,0.0003409742,0.000131912,0.6342157,0.02955548,0.01068484,0.00199571,0.00006068105],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9807092,0.0001554151,0.01679499,0.00008252225,0.00000332848,0.00001277621,0.001217972,0.000151719,0.0008721097],"genre_scores_gemma":[0.9963878,0.00006633651,0.002329331,0.0000161704,0.000002022944,0.00002103086,0.0006487988,0.00001163984,0.0005168451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002911017,"threshold_uncertainty_score":0.005788147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202797504815802,"score_gpt":0.2572537295887614,"score_spread":0.2352257545406034,"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."}}