{"id":"W4401516941","doi":"10.1186/s13059-024-03351-2","title":"Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells","year":2024,"lang":"en","type":"article","venue":"Genome biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Burroughs Wellcome Fund; University of California, San Diego; York University; University of Pennsylvania; Genentech","keywords":"Biology; Human genetics; Adaptation (eye); Gene; Genome Biology; Computational biology; Genetics; Regulation of gene expression; Gene regulatory network; Evolutionary biology; Genomics; Gene expression; Genome; Neuroscience","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":[0.0007651293,0.0002982188,0.0005591186,0.000438691,0.0002156848,0.00061898,0.000383817,0.0003249345,0.0007147037],"category_scores_gemma":[0.001834876,0.0001859495,0.0005150386,0.0006048137,0.0007378809,0.0004621881,0.0004663757,0.000518098,0.0001472939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005996376,"about_ca_system_score_gemma":0.0002871816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008763432,"about_ca_topic_score_gemma":0.001100557,"domain_scores_codex":[0.9995402,0.00006675895,0.00003241486,0.0002283244,0.00009974822,0.00003259056],"domain_scores_gemma":[0.99871,0.0006403503,0.0002927382,0.0002115245,0.00008655561,0.00005872523],"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":[0.0003501824,0.00009357939,0.07148991,0.000477381,0.0003021832,0.0002084566,0.0001188926,0.1060557,0.7991061,0.003966197,0.0004495661,0.0173818],"study_design_scores_gemma":[0.00003117607,0.0002643202,0.2543924,0.00004037682,0.0002638728,0.0005841122,0.0002176919,0.4636901,0.260916,0.01599445,0.00352315,0.00008250707],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600707,0.000483511,0.03627234,0.00007572854,0.000006721104,0.00002045409,0.001948885,0.0002815651,0.0008400491],"genre_scores_gemma":[0.9897252,0.0002207281,0.007308734,0.00005487429,0.000005479337,0.000047053,0.002494231,0.00003553491,0.0001081371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008763432,"threshold_uncertainty_score":0.004350722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02219937610083292,"score_gpt":0.2306448716567915,"score_spread":0.2084454955559586,"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."}}