{"id":"W2132680932","doi":"10.1074/jbc.m502332200","title":"Elucidation of Gene-to-Gene and Metabolite-to-Gene Networks inArabidopsis by Integration of Metabolomics andTranscriptomics","year":2005,"lang":"en","type":"article","venue":"Journal of Biological Chemistry","topic":"Genomics, phytochemicals, and oxidative stress","field":"Biochemistry, Genetics and Molecular Biology","cited_by":475,"is_retracted":false,"has_abstract":true,"ca_institutions":"Phenomenome Discoveries (Canada)","funders":"Core Research for Evolutional Science and Technology; Japan Science and Technology Agency","keywords":"Gene; Biology; Gene cluster; Genome; Transcriptome; Proteomics; Genetics; Gene regulatory network; Functional genomics; Genomics; Arabidopsis; Computational biology; Metabolomics; Gene expression; Mutant; Bioinformatics","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":[0.0003894329,0.0002269852,0.0005259005,0.0000446025,0.00003261701,0.00001412704,0.0002982309,0.0003341237,0.00001428922],"category_scores_gemma":[0.0002563235,0.0001827884,0.00018842,0.0001358321,0.0001406527,0.00001135795,0.00008031235,0.0001896461,4.344093e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002584258,"about_ca_system_score_gemma":0.00004451692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003395448,"about_ca_topic_score_gemma":0.000001058418,"domain_scores_codex":[0.9984909,0.00005664825,0.0007895432,0.0002977776,0.0001419137,0.0002232764],"domain_scores_gemma":[0.9986361,0.00003051728,0.0005157994,0.0002246368,0.0003794075,0.0002135595],"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":[0.0005084813,0.0001333257,0.001091857,0.00001646697,0.0001132168,5.234216e-7,0.00005064551,0.0006870318,0.9929872,0.000003422934,0.0003687129,0.004039183],"study_design_scores_gemma":[0.0005849386,0.0002869218,0.00176051,0.00001539485,0.00006604017,0.00002758807,0.00007657654,0.00007808351,0.9937996,0.00003745599,0.003080823,0.0001860677],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711783,0.004583554,0.02361707,0.0001766486,0.00007048325,0.0001226047,0.0001816455,0.000003134487,0.00006659124],"genre_scores_gemma":[0.9779319,0.002349718,0.01877738,0.0002340473,0.0004395124,0.000005052751,0.000208018,0.00001440435,0.00003993597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006753662,"threshold_uncertainty_score":0.7453896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318204987724938,"score_gpt":0.245013033789449,"score_spread":0.2318309839121996,"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."}}