The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Index and biological spectrum of human DNase I hypersensitive sites
Open accessPublished version of a preprint
Abstract
DNase I hypersensitive sites (DHSs) are generic markers of regulatory DNA 1–5 and contain genetic variations associated with diseases and phenotypic traits 6–8 . We created high-resolution maps of DHSs from 733 human biosamples encompassing 438 cell and tissue types and states, and integrated these to delineate and numerically index approximately 3.6 million DHSs within the human genome sequence, providing a common coordinate system for regulatory DNA. Here we show that these maps highly resolve the cis -regulatory compartment of the human genome, which encodes unexpectedly diverse cell- and tissue-selective regulatory programs at very high density. These programs can be captured comprehensively by a simple vocabulary that enables the assignment to each DHS of a regulatory barcode that encapsulates its tissue manifestations, and global annotation of protein-coding and non-coding RNA genes in a manner orthogonal to gene expression. Finally, we show that sharply resolved DHSs markedly enhance the genetic association and heritability signals of diseases and traits. Rather than being confined to a small number of distal elements or promoters, we find that genetic signals converge on congruently regulated sets of DHSs that decorate entire gene bodies. Together, our results create a universal, extensible coordinate system and vocabulary for human regulatory DNA marked by DHSs, and provide a new global perspective on the architecture of human gene regulation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, open chromatin regions are not limited to active enhancers, and also harbour other regions including active gene promoters, regulatory elements in a ‘poised’ chromatin configuration (discussed below), as well as some structural regions such as tissue-invariant binding sites for the architectural protein CCCTC-binding factor (CTCF) [129–132].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [130]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“A majority of TCs (90%) were supported by FANTOM5 CAGE peaks17 and/or open chromatin regions from ENCODE22 and TCGA7”
From Alternative promoters in CpG depleted regions are prevalently associated with epigenetic misregulation of liver cancer transcriptomes (2023) · cites this paper as [22]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Learning the parts of objects by non-negative matrix factorization
Lee, D. D., & Seung, H. S. (1999) · Nature · doi:10.1038/44565 · Cited by 14,193
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Self-citationLD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
The approximation of one matrix by another of lower rank
Eckart, C., & Young, G. (1936) · Psychometrika · doi:10.1007/bf02288367 · Cited by 4,497
FIMO: scanning for occurrences of a given motif
Grant, C. E., Bailey, T. L., & Noble, W. S. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr064 · Cited by 4,247
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
Self-citationThe Human Transcription Factors
Lambert, S. A., Jolma, A., Campitelli, L. F., Das, P. K., Yin, Y., Albu, M., Chen, X., Taipale, J., Hughes, T. R., & Weirauch, M. T. (2018) · Cell · doi:10.1016/j.cell.2018.01.029 · Cited by 3,399
GENCODE reference annotation for the human and mouse genomes
Frankish, A., Diekhans, M., Ferreira, A.-M., Johnson, R., Jungreis, I., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J. C., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky955 · Cited by 3,006
Mapping and analysis of chromatin state dynamics in nine human cell types
Ernst, J., Kheradpour, P., Mikkelsen, T. S., Shoresh, N., Ward, L. D., Epstein, C. B., Zhang, X., Wang, L., Issner, R., Coyne, M., et al. (2011) · Nature · doi:10.1038/nature09906 · Cited by 2,898
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679
Self-citationPartitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604
Detection of nonneutral substitution rates on mammalian phylogenies
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R., & Siepel, A. (2010) · Genome Research · doi:10.1101/gr.097857.109 · Cited by 2,353
The UCSC Table Browser data retrieval tool
Karolchik, D. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh103 · Cited by 2,314
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Loh, P.-R., Tucker, G., Bulik-Sullivan, B. K., Vilhjálmsson, B. J., Finucane, H. K., Salem, R. M., Chasman, D. I., Ridker, P. M., Neale, B. M., Berger, B., et al. (2015) · Nature Genetics · doi:10.1038/ng.3190 · Cited by 1,507
High-Resolution Mapping and Characterization of Open Chromatin across the Genome
Boyle, A. P., Davis, S., Shulha, H. P., Meltzer, P., Margulies, E. H., Weng, Z., Furey, T. S., & Crawford, G. E. (2008) · Cell · doi:10.1016/j.cell.2007.12.014 · Cited by 1,415
NUCLEASE HYPERSENSITIVE SITES IN CHROMATIN
Gross, D. S., & Garrard, W. T. (1988) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.57.070188.001111 · Cited by 1,233
The 5′ ends of Drosophila heat shock genes in chromatin are hypersensitive to DNase I
Wu, C. C. M. (1980) · Nature · doi:10.1038/286854a0 · Cited by 1,118
Finucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., Gazal, S., Loh, P.-R., Lareau, C., Shoresh, N., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0081-4 · Cited by 1,097
BEDOPS: high-performance genomic feature operations
Neph, S. J., Kuehn, M. S., Reynolds, A. P., Haugen, E., Thurman, R. E., Johnson, A., Rynes, E., Maurano, M. T., Vierstra, J. D., Thomas, S., et al. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts277 · Cited by 971
Self-citationChromatin accessibility pre-determines glucocorticoid receptor binding patterns
John, S., Sabo, P. J., Thurman, R. E., Sung, M.-H., Biddie, S. C., Johnson, T. A., Hager, G. L., & Stamatoyannopoulos, J. A. (2011) · Nature Genetics · doi:10.1038/ng.759 · Cited by 954
Self-citationChung, J. H., Whiteley, M., & Felsenfeld, G. (1993) · Cell · doi:10.1016/0092-8674(93)80052-g · Cited by 854
SVD based initialization: A head start for nonnegative matrix factorization
Boutsidis, C., & Gallopoulos, E. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.09.010 · Cited by 729
Defining functional DNA elements in the human genome
Kellis, M., Wold, B. J., Snyder, M. P., Bernstein, B., Kundaje, A. B., Marinov, G. K., Ward, L. D., Birney, E., Crawford, G. E., Dekker, J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1318948111 · Cited by 724
Self-citationMassive mining of publicly available RNA-seq data from human and mouse
Lachmann, A., Torre, D., Keenan, A. B., Jagodnik, K. M., Lee, H. J., Wang, L., Silverstein, M. C., & Ma’ayan, A. (2018) · Nature Communications · doi:10.1038/s41467-018-03751-6 · Cited by 701
KRAB zinc-finger proteins contribute to the evolution of gene regulatory networks
Imbeault, M., Helleboid, P.-Y., & Trono, D. (2017) · Nature · doi:10.1038/nature21683 · Cited by 623
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J., & Noble, W. S. (2012) · Nature Methods · doi:10.1038/nmeth.1937 · Cited by 566
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544
Song, L., Zhang, Z., Grasfeder, L. L., Boyle, A. P., Giresi, P. G., Lee, B.-K., Sheffield, N. C., Gräf, S., Huss, M., Keefe, D., et al. (2011) · Genome Research · doi:10.1101/gr.121541.111 · Cited by 517
Approximately independent linkage disequilibrium blocks in human populations
Berisa, T., & Pickrell, J. K. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv546 · Cited by 500
Targeted RNA sequencing reveals the deep complexity of the human transcriptome
Mercer, T. R., Gerhardt, D. J., Dinger, M. E., Crawford, J., Trapnell, C., Jeddeloh, J. A., Mattick, J. S., & Rinn, J. L. (2011) · Nature Biotechnology · doi:10.1038/nbt.2024 · Cited by 490
Determinants and dynamics of genome accessibility
Bell, O., Tiwari, V. K., Thomä, N. H., & Schübeler, D. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3017 · Cited by 481
Tissue-specific DNA cleavages in the globin chromatin domain introduced by DNAase I
Stalder, J. (1980) · Cell · doi:10.1016/0092-8674(80)90631-5 · Cited by 474
Li, Q., Peterson, K. R., Fang, X., & Stamatoyannopoulos, G. (2002) · Blood · doi:10.1182/blood-2002-04-1104 · Cited by 456
Concepts, estimation and interpretation of SNP-based heritability
Yang, J., Zeng, J., Goddard, M. E., Wray, N. R., & Visscher, P. M. (2017) · Nature Genetics · doi:10.1038/ng.3941 · Cited by 455
Klann, T. S., Black, J. B., Chellappan, M., Safi, A., Song, L., Hilton, I. B., Crawford, G. E., Reddy, T. E., & Gersbach, C. A. (2017) · Nature Biotechnology · doi:10.1038/nbt.3853 · Cited by 447
McGhee, J. D. (1981) · Cell · doi:10.1016/0092-8674(81)90359-7 · Cited by 432
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J., & Noble, W. S. (2012) · eScholarship@UMassChan · Cited by 397
Global reference mapping of human transcription factor footprints
Vierstra, J., Lazar, J., Sandstrom, R., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Haugen, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2528-x · Cited by 386
Self-citationThe Majority of Primate-Specific Regulatory Sequences Are Derived from Transposable Elements
Jacques, P., Jeyakani, J., & Bourque, G. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003504 · Cited by 360
The GENCODE pseudogene resource
Pei, B., Sisu, C., Frankish, A., Howald, C., Habegger, L., Mu, X. J., Harte, R., Balasubramanian, S., Andrea Tanzer, A., Diekhans, M., et al. (2012) · Genome biology · doi:10.1186/gb-2012-13-9-r51 · Cited by 356
Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes
Stergachis, A. B., Neph, S. J., Reynolds, A. P., Humbert, R., Miller, B., Paige, S. L., Vernot, B., Cheng, J. B., Thurman, R. E., Sandstrom, R. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.07.020 · Cited by 343
Self-citationUnsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J. A., & Noble, W. S. (2013) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2506583.2506701 · Cited by 288
Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution
Vierstra, J. D., Rynes, E., Sandstrom, R. S., Zhang, M., Canfield, T. K., Hansen, R. S., Stehling-Sun, S., Sabo, P. J., Byron, R., Humbert, R., et al. (2014) · Science · doi:10.1126/science.1246426 · Cited by 263
Self-citationEnter the Matrix: Factorization Uncovers Knowledge from Omics
Stein-O’Brien, G., Arora, R., Culhane, A. C., Favorov, A. V., Garmire, L. X., Greene, C. S., Goff, L. A., Li, Y., Ngom, A., Ochs, M. F., et al. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.07.003 · Cited by 228
Conservation of trans-acting circuitry during mammalian regulatory evolution
Stergachis, A. B., Neph, S., Sandstrom, R., Haugen, E., Reynolds, A. P., Zhang, M., Byron, R., Canfield, T., Stelhing-Sun, S., Lee, K., et al. (2014) · Nature · doi:10.1038/nature13972 · Cited by 212
Self-citationIdentifying gene regulatory elements by genome-wide recovery of DNase hypersensitive sites
Crawford, G. E., Holt, I. E., Mullikin, J. C., Tai, D. S., Green, E. D., Wolfsberg, T. G., & Collins, F. S. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307540100 · Cited by 184
Gazal, S., Loh, P.-R., Finucane, H. K., Ganna, A., Schoech, A., Sunyaev, S., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0231-8 · Cited by 154
Discovery of functional noncoding elements by digital analysis of chromatin structure
Sabo, P. J., Hawrylycz, M., Wallace, J. C., Humbert, R., Yu, M., Shafer, A., Kawamoto, J., Hall, R., Mack, J., Dorschner, M. O., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407387101 · Cited by 139
Self-citationFunctional footprinting of regulatory DNA
Vierstra, J., Reik, A., Chang, K.-H., Stehling-Sun, S., Zhou, Y., Hinkley, S. J., Paschon, D. E., Zhang, L., Psatha, N., Bendana, Y. R., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3554 · Cited by 133
Self-citationShibata, Y., Sheffield, N. C., Fedrigo, O. D., Babbitt, C. C., Wortham, M., Tewari, A. K., London, D., Song, L., Lee, B., Iyer, V. R., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002789 · Cited by 124
DNase I hypersensitive sites in the chromatin of human μ immunoglobulin heavy-chain genes
Mills, F. C., Fisher, L. M., Kuroda, R., Ford, A. M., & Gould, H. J. (1983) · Nature · doi:10.1038/306809a0 · Cited by 104
Genome‐Scale Mapping of DNase I Hypersensitivity
John, S., Sabo, P. J., Canfield, T. K., Lee, K., Vong, S., Weaver, M., Wang, H., Vierstra, J. D., Reynolds, A. P., Thurman, R. E., et al. (2013) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2127s103 · Cited by 96
Self-citationComparative analysis of pseudogenes across three phyla
Sisu, C., Pei, B., Leng, J., Frankish, A., Zhang, Y., Balasubramanian, S., Harte, R., Wang, D., Rutenberg-Schoenberg, M., Clark, W. T., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1407293111 · Cited by 95
Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk
Reshef, Y. A., Finucane, H. K., Kelley, D. R., Gusev, A., Kotliar, D., Ulirsch, J. C., Hormozdiari, F., Nasser, J., O’Connor, L., van de Geijn, B., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0196-7 · Cited by 68
Fast analysis of scATAC-seq data using a predefined set of genomic regions
Giansanti, V., Tang, M., & Cittaro, D. (2020) · F1000Research · doi:10.12688/f1000research.22731.1 · Cited by 16
Cited by
Sorted by citations
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2493-4 · Cited by 2,378
Self-citationA cross-population atlas of genetic associations for 220 human phenotypes
Sakaue, S., Kanai, M., Tanigawa, Y., Karjalainen, J. M., Kurki, M., Koshiba, S., Narita, A., Konuma, T., Yamamoto, K., Akiyama, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00931-x · Cited by 2,335
Demontis, D., Walters, G. B., Athanasiadis, G., Walters, R., Therrien, K., Nielsen, T. T., Farajzadeh, L., Voloudakis, G., Bendl, J., Zeng, B., et al. (2022) · Nature Genetics · doi:10.1016/j.euroneuro.2022.07.018 · Cited by 863
SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks
Bravo González-Blas, C., De Winter, S., Hulselmans, G., Hecker, N., Matetovici, I., Christiaens, V., Poovathingal, S., Wouters, J., Aibar, S., & Aerts, S. (2023) · Nature Methods · doi:10.1038/s41592-023-01938-4 · Cited by 778
Nucleotide Transformer: building and evaluating robust foundation models for human genomics
Dalla-Torre, H., Gonzalez, L., Mendoza-Revilla, J., Lopez Carranza, N., Grzywaczewski, A. H., Oteri, F., Dallago, C., Trop, E., de Almeida, B. P., Sirelkhatim, H., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02523-z · Cited by 772
“Enhancers were split in tissue-specific and tissue-invariant based on the vocabulary from Meuleman et al. 33 (https://www.meuleman.org/research/dhsin-dex/).”
Metadata
- Authors
- Meuleman, W., Muratov, A., Rynes, E., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Teodosiadis, A., Reynolds, A., Haugen, E., Nelson, J., Johnson, A., Frerker, M., Buckley, M., Sandstrom, R., Vierstra, J., Kaul, R., & Stamatoyannopoulos, J.
- Affiliations
- Altius Institute for Biomedical Sciences (US)
- University of Washington (US)
- Corresponding author
- Meuleman, Wouter
- Stamatoyannopoulos, John
- ORCID
- Venue
- Nature
- Published
- 2020-07-29
- Volume
- 584
- Issue
- 7820
- Pages
- 244-251
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7422677
- OpenAlex
- W3046013264
- Cited by
- 331
- References
- 60
- Citations by year
- 2026: 40 · 2025: 59 · 2024: 61 · 2023: 58 · 2022: 56 · 2021: 43 · 2020: 14
- Type
- paratext
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Human Genome Research Institute (U54HG007010, UM1HG009444, R35HG011317)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- DNase I hypersensitive sites, cis-regulatory elements, genetic association signals, heritability
- MeSH terms
- Chromatin, Deoxyribonuclease I, DNA, Gene Expression Regulation, Genes, Humans, Promoter Regions, Genetic, Regulatory Sequences, Nucleic Acid, Genome, Human, Molecular Sequence Annotation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review