{"id":"W4392975641","doi":"10.1016/j.cmet.2024.02.015","title":"Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy","year":2024,"lang":"en","type":"article","venue":"Cell Metabolism","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; Chinook Therapeutics; National Institute on Aging; Pfizer","keywords":"Transcriptome; Metabolomics; Biology; Epigenomics; Computational biology; Chromatin; Cell type; Cell biology; Cell; Bioinformatics; Gene expression; Gene; Genetics","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":[0.0003174549,0.00025465,0.0004374848,0.000884963,0.0002602661,0.0006657172,0.0001984204,0.0002909157,0.001452414],"category_scores_gemma":[0.0003079641,0.0002162973,0.0003882502,0.0008053776,0.0002615472,0.0003215383,0.0004989564,0.0002990502,0.0004352393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001677095,"about_ca_system_score_gemma":0.0003372951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134161,"about_ca_topic_score_gemma":0.004115316,"domain_scores_codex":[0.9998063,0.00003163763,0.000009791314,0.0000874625,0.00004543782,0.00001936781],"domain_scores_gemma":[0.9998467,0.00004457284,0.00003332289,0.00003325378,0.00002666932,0.00001532192],"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":[0.0001812227,0.00002001651,0.03399205,0.0002896471,0.0001540207,0.0001566434,0.0001783464,0.001572105,0.9267592,0.0006389007,0.0004773279,0.03558052],"study_design_scores_gemma":[0.00002036375,0.0002368455,0.5416927,0.00007536395,0.0003692084,0.001922902,0.000615967,0.01592307,0.4110321,0.003966193,0.02407055,0.00007473982],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8209751,0.004957895,0.1547872,0.00037527,0.00004578578,0.00007426112,0.01479177,0.0008766997,0.003116141],"genre_scores_gemma":[0.9326678,0.0026502,0.05604161,0.0001896922,0.00003269182,0.0001050186,0.006420658,0.0001885361,0.001703813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001452414,"threshold_uncertainty_score":0.004858792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261788954132727,"score_gpt":0.2397082372218561,"score_spread":0.2270903476805289,"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."}}