Data storage using peptide sequences
Open accessAbstract
Humankind is generating digital data at an exponential rate. These data are typically stored using electronic, magnetic or optical devices, which require large physical spaces and cannot last for a very long time. Here we report the use of peptide sequences for data storage, which can be durable and of high storage density. With the selection of suitable constitutive amino acids, designs of address codes and error-correction schemes to protect the order and integrity of the stored data, optimization of the analytical protocol and development of a software to effectively recover peptide sequences from the tandem mass spectra, we demonstrated the feasibility of this method by successfully storing and retrieving a text file and the music file Silent Night with 40 and 511 18-mer peptides respectively. This method for the first time links data storage with the peptide synthesis industry and proteomics techniques, and is expected to stimulate the development of relevant fields.
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
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?
Apart from DNA, other organic molecules have been proposed for data storage, including peptide sequences and urethanes.
“Apart from DNA, other organic molecules have been recently proposed.133,134 Two interesting examples are the use of peptide sequences for data storage, as reported by Ng et al.133 and the use of urethanes as reported by Dahlhauser et al.134”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [133]
In both peptide and urethane data storage cases, reading required the use of mass spectroscopy, with consequent limitations in costs and speed.
“Unfortunately in both these cases, reading required the use of mass spectroscopy, with the consequent limitation in terms of costs and speed.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [133]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A cross-platform toolkit for mass spectrometry and proteomics
Chambers, M., MacLean, B., Burke, R., Amodei, D., Ruderman, D., Neumann, S., Gatto, L., Fischer, B., Pratt, B. S., Egertson, J. D., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2377 · Cited by 4,042 · see citing works
Polynomial Codes Over Certain Finite Fields
Reed, I. S., & Solomon, G. (1960) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0108018 · Cited by 3,693 · see citing works
Near Shannon limit performance of low density paritycheck codes
Mackay, D., & Neal, R. M. (1997) · Electronics Letters · doi:10.1049/el:19970362 · Cited by 2,694 · see citing works
Mass-spectrometric exploration of proteome structure and function
Aebersold, R., & Mann, M. (2016) · Nature · doi:10.1038/nature19949 · Cited by 2,334 · see citing works
The World’s Technological Capacity to Store, Communicate, and Compute Information
Hilbert, M., & López, P. (2011) · Science · doi:10.1126/science.1200970 · Cited by 1,643 · see citing works
Next-Generation Digital Information Storage in DNA
Church, G. M., Gao, Y., & Kosuri, S. (2012) · Science · doi:10.1126/science.1226355 · Cited by 1,441 · see citing works
PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry
Ma, B., Zhang, K., Hendrie, C., Liang, C., Li, M., Doherty‐Kirby, A., & Lajoie, G. (2003) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.1196 · Cited by 1,382 · see citing works
Towards Practical, High-Capacity, Low-Maintenance Information Storage in Synthesized DNA
Goldman, N., Bertone, P., Chen, S., Dessimoz, C., LeProust, E. M., Sipos, B., & Birney, E. (2013) · Nature · doi:10.1038/nature11875 · Cited by 1,220 · see citing works
DNA Fountain enables a robust and efficient storage architecture
Erlich, Y., & Zielinski, D. (2017) · Science · doi:10.1126/science.aaj2038 · Cited by 898 · see citing works
Ryan, W. E., & Lin, S. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511803253 · Cited by 778 · see citing works
Random access in large-scale DNA data storage
Organick, L., Ang, S. D., Chen, Y.-J., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4079 · Cited by 775 · see citing works
Robust Chemical Preservation of Digital Information on DNA in Silica with Error-Correcting Codes
Grass, R. N., Heckel, R., Puddu, M., Paunescu, D., & Stark, W. J. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201411378 · Cited by 754 · see citing works
Hiding messages in DNA microdots
Clelland, C. T., Risca, V. I., & Bancroft, C. (1999) · Nature · doi:10.1038/21092 · Cited by 638 · see citing works
Paving the way to single-molecule protein sequencing
Restrepo-Pérez, L., Joo, C., & Dekker, C. (2018) · Nature Nanotechnology · doi:10.1038/s41565-018-0236-6 · Cited by 397 · see citing works
A DNA-Based Archival Storage System
Bornholt, J., Lopez, R. M., Carmean, D. M., Ceze, L., Seelig, G., & Strauß, K. (2016) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/2872362.2872397 · Cited by 346 · see citing works
Design and synthesis of digitally encoded polymers that can be decoded and erased
Roy, R. K., Meszyńska, A., Laure, C., Charles, L., Verchin, C., & Lutz, J. (2015) · Nature Communications · doi:10.1038/ncomms8237 · Cited by 309 · see citing works
Cleavage N-Terminal to Proline: Analysis of a Database of Peptide Tandem Mass Spectra
Breci, L. A., Tabb, D. L., Yates, J. R., & Wysocki, V. H. (2003) · Analytical Chemistry · doi:10.1021/ac026359i · Cited by 307 · see citing works
GutenTag: High-Throughput Sequence Tagging via an Empirically Derived Fragmentation Model
Tabb, D. L., Saraf, A., & Yates, J. R. (2003) · Analytical Chemistry · doi:10.1021/ac0347462 · Cited by 274 · see citing works
Trauger, S. A., Go, E. P., Shen, Z., Apon, J. V., Compton, B. J., Bouvier, E. S. P., Finn, M. G., & Siuzdak, G. E. (2004) · Analytical Chemistry · doi:10.1021/ac049657j · Cited by 235 · see citing works
De novo sequencing of peptides by MS/MS
Seidler, J., Zinn, N., Boehm, M. E., & Lehmann, W. D. (2009) · PROTEOMICS · doi:10.1002/pmic.200900459 · Cited by 221 · see citing works
Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures
Swaminathan, J., Boulgakov, A. A., Hernandez, E. T., Bardo, A. M., Bachman, J. L., Marotta, J., Johnson, A. M., Anslyn, E. V., & Marcotte, E. M. (2018) · Nature Biotechnology · doi:10.1038/nbt.4278 · Cited by 219 · see citing works
Attomole-Sensitivity Electrospray Source for Large-Molecule Mass Spectrometry
Valaskovic, G. A., Kelleher, N. L., Little, D. P., Aaserud, D. J., & McLafferty, F. W. (1995) · Analytical Chemistry · doi:10.1021/ac00116a030 · Cited by 217 · see citing works
Lessons in de novo peptide sequencing by tandem mass spectrometry
Medzihradszky, K. F., & Chalkley, R. J. (2013) · Mass Spectrometry Reviews · doi:10.1002/mas.21406 · Cited by 206 · see citing works
De Novo Peptide Sequencing and Identification with Precision Mass Spectrometry
Frank, A. M., Savitski, M. M., Nielsen, M. L., Zubarev, R. A., & Pevzner, P. A. (2006) · Journal of Proteome Research · doi:10.1021/pr060271u · Cited by 196 · see citing works
Tabb, D. L., Huang, Y., Wysocki, V. H., & Yates, J. R. (2004) · Analytical Chemistry · doi:10.1021/ac0351163 · Cited by 153 · see citing works
Probing the physical limits of reliable DNA data retrieval.
Organick, L., Chen, Y.-J., Dumas Ang, S., Lopez, R., Liu, X., Strauss, K., & Ceze, L. (2020) · Nature Communications · doi:10.1038/s41467-020-14319-8 · Cited by 135 · see citing works
The Revolution and Evolution of Shotgun Proteomics for Large-Scale Proteome Analysis
Yates, J. R. (2013) · Journal of the American Chemical Society · doi:10.1021/ja3094313 · Cited by 131 · see citing works
DirecTag: Accurate Sequence Tags from Peptide MS/MS through Statistical Scoring
Tabb, D. L., Ma, Z., Martin, D. B., Ham, A. L., & Chambers, M. (2008) · Journal of Proteome Research · doi:10.1021/pr800154p · Cited by 129 · see citing works
Automated de novo protein sequencing of monoclonal antibodies
Bandeira, N., Pham, V. C., Pevzner, P. A., Arnott, D. P., & Lill, J. R. (2008) · Nature Biotechnology · doi:10.1038/nbt1208-1336 · Cited by 128 · see citing works
Binary tree-inspired digital dendrimer
Huang, Z., Shi, Q., Guo, J., Meng, F., Zhang, Y., Lu, Y., Qian, Z., Li, X., Zhou, N., Zhang, Z., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09957-6 · Cited by 109 · see citing works
Storage of Information Using Small Organic Molecules
Cafferty, B. J., Ten, A. S., Fink, M. J., Morey, S., Preston, D. J., Mrksich, M., & Whitesides, G. M. (2019) · ACS Central Science · doi:10.1021/acscentsci.9b00210 · Cited by 107 · see citing works
Strategies for Development of a Next-Generation Protein Sequencing Platform
Callahan, N., Tullman, J. A., Kelman, Z., & Marino, J. P. (2019) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2019.09.005 · Cited by 73 · see citing works
A DNA-Based Archival Storage System
Bornholt, J., Lopez, R., Carmean, D. M., Ceze, L., Seelig, G., & Strauss, K. (2016) · ACM SIGPLAN Notices · doi:10.1145/2954679.2872397 · Cited by 54 · see citing works
A model-based method for the prediction of the isotopic distribution of peptides
Valkenborg, D., Jansen, I., & Burzykowski, T. (2008) · Journal of the American Society for Mass Spectrometry · doi:10.1016/j.jasms.2008.01.009 · Cited by 46 · see citing works
Sun, B., Kovatch, J. R., Badiong, A., & Merbouh, N. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00416 · Cited by 35 · see citing works
Nguyen, T. T. T. N., Petersen, N. J., & Rand, K. D. (2016) · Analytica Chimica Acta · doi:10.1016/j.aca.2016.07.002 · Cited by 33 · see citing works
NovoHCD: De novo Peptide Sequencing From HCD Spectra
Yan, Y., KUSALIK, A. J., & Wu, F. (2014) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2014.2316424 · Cited by 14 · see citing works
Move over, DNA: ancient proteins are starting to reveal humanity’s history
Warren, M. (2019) · Nature · doi:10.1038/d41586-019-01986-x · Cited by 14 · see citing works
Service, R. F. (2015) · Science · doi:10.1126/science.349.6246.372 · Cited by 7 · see citing works
Data storage using peptide sequencesPreprint
Ng, C. C. A., Tam, W. M., Yin, H., Wu, Q., So, P., Wong, M. Y., Lau, F. C. M., & Yao, Z. (2021) · Research Square · doi:10.21203/rs.3.pex-1543/v1 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
1 of the 41 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Emerging Approaches to DNA Data Storage: Challenges and Prospects
Doricchi, A., Platnich, C. M., Gimpel, A., Horn, F., Earle, M., Lanzavecchia, G., Cortajarena, A. L., Liz-Marzán, L. M., Liu, N., Heckel, R., et al. (2022) · ACS Nano · doi:10.1021/acsnano.2c06748 · Cited by 235 · see citing works
Biomimetic Metallic Nanostructures for Biomedical Applications, Catalysis, and Beyond
Yaraki, M. T., Nasab, S. Z., Zare, I., Dahri, M., Sadeghi, M. M., Koohi, M., & Tan, Y. N. (2022) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.2c00285 · Cited by 115 · see citing works
Abiotic peptides as carriers of information for the encoding of small-molecule library synthesis
Rössler, S. L., Grob, N. M., Buchwald, S. L., & Pentelute, B. L. (2023) · Science · doi:10.1126/science.adf1354 · Cited by 51 · see citing works
Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review
Ng, C. C. A., Zhou, Y. Z., & Yao, Z. (2023) · Analytica Chimica Acta · doi:10.1016/j.aca.2023.341330 · Cited by 44 · see citing works
Self-citationLu, J., Guo, Z., Huang, W. T., Bao, M., He, B., Li, G., Lei, J., & Lei, J. (2023) · Talanta · doi:10.1016/j.talanta.2023.125261 · Cited by 32 · see citing works
Peptide-Based Sensing, Logic Computing, and Information Security on the Antimonene Platform
Bu, Z. Q., Yao, Q. F., Liu, Q. Y., Quan, M. X., Lu, J., & Huang, W. T. (2022) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.1c23814 · Cited by 32 · see citing works
Preservation and Encryption in DNA Digital Data Storage
Zhang, Y., Ren, Y., Liu, Y., Wang, F., Zhang, H., & Liu, K. (2022) · ChemPlusChem · doi:10.1002/cplu.202200183 · Cited by 28 · see citing works
Liu, Q. Y., Bu, Z. Q., Quan, M. X., Wu, Y., Ding, X., Xia, L. Q., Lu, J., & Huang, W. T. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114260 · Cited by 27 · see citing works
Robotic synthesis of peptides containing metal-oxide-based amino acids
She, S., Bell, N. L., Zheng, D., Mathieson, J. S., Castro, M. D., Long, D., Koehnke, J., & Cronin, L. (2022) · Chem · doi:10.1016/j.chempr.2022.07.007 · Cited by 25 · see citing works
How to make DNA data storage more applicable
Akash, A., Bencúrová, E., & Dandekar, T. (2023) · Trends in biotechnology · doi:10.1016/j.tibtech.2023.07.006 · Cited by 23 · see citing works
Mirror-image trypsin digestion and sequencing of D-proteins
Zhang, G., & Zhu, T. F. (2024) · Nature Chemistry · doi:10.1038/s41557-023-01411-x · Cited by 22 · see citing works
DNA storage: The future direction for medical cold data storage
Shen, P., Zheng, Y., Zhang, C., Li, S., Chen, Y., Chen, Y., Liu, Y., & Cai, Z. (2025) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2025.03.006 · Cited by 18 · see citing works
Molecular data storage with zero synthetic effort and simple read-out
Bohn, P., Weisel, M. P., Wolfs, J., & Meier, M. A. R. (2022) · Scientific Reports · doi:10.1038/s41598-022-18108-9 · Cited by 17 · see citing works
Nanopore Deciphering Single Digital Polymers Towards High‐Density Data Storage
Hu, Z., Liu, Y., Xin, K., Yu, R., Zhang, L., & Ying, Y. (2023) · Chemistry - A European Journal · doi:10.1002/chem.202203919 · Cited by 16 · see citing works
Fabrication and Decryption of a Microarray of Digital Dithiosuccinimide Oligomers
Shi, Q., Miao, T., Liu, Y., Hu, L., Yang, H., Shen, H., Piao, M., Huang, Z., & Zhang, Z. (2022) · Macromolecular Rapid Communications · doi:10.1002/marc.202200029 · Cited by 16 · see citing works
Isotope Ratio Encoding of Sequence-Defined Oligomers
Zwillinger, M., Fischer, L., Sályi, G., Szabó, S., Csékei, M., Huc, I., & Kotschy, A. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c08135 · Cited by 15 · see citing works
Digital Polymers Based on Cyclic Monomers
Ren, X., Ding, H., Li, S., & Zhang, K. (2024) · Macromolecules · doi:10.1021/acs.macromol.3c02405 · Cited by 15 · see citing works
The bottom of the memory hierarchy: Semiconductor and DNA data storage
Kim, S. J., Jung, W., Jung, H. S., Lee, M., Heo, J., Horgan, A. M., Godron, X., & Ham, D. (2023) · MRS Bulletin · doi:10.1557/s43577-023-00510-x · Cited by 12 · see citing works
Zhang, L., Krause, T. B., Deol, H., Pandey, B., Xiao, Q., Park, H. M., Iverson, B. L., Law, D., & Anslyn, E. V. (2024) · Chemical Science · doi:10.1039/d3sc06189b · Cited by 11 · see citing works
Data Readout Techniques for DNA‐Based Information Storage
Liu, B., Wang, F., Fan, C., & Li, Q. (2025) · Advanced Materials · doi:10.1002/adma.202412926 · Cited by 12 · see citing works
Kaygisiz, K., & Ulijn, R. V. (2025) · ChemSystemsChem · doi:10.1002/syst.202400075 · Cited by 8 · see citing works
Lu, J., Bu, Z. Q., & Huang, W. T. (2022) · Microchemical Journal · doi:10.1016/j.microc.2022.108198 · Cited by 7 · see citing works
Advances in protein sequencing: Techniques, challenges and prospects
Luo, X., Ng, C. C. A., Lam, H., & Yao, Z. (2025) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2025.118341 · Cited by 7 · see citing works
Self-citationAsche, S., Pow, R., Mehr, S. H. M., Cooper, G. J. T., Sharma, A., & Cronin, L. (2024) · ChemSystemsChem · doi:10.1002/syst.202400006 · Cited by 7 · see citing works
Zhang, A., Wang, L.-J., Zhai, X., Xiao, Y., Wu, Y., Zhao, Y., Liu, K., Zheng, J., & Chen, D. (2025) · Advanced Science · doi:10.1002/advs.202503790 · Cited by 6 · see citing works
Exploring the intersection of natural sciences and information technology via entropy and randomness
Luescher, A. M., Heckel, R., & Grass, R. N. (2025) · Nature Communications · doi:10.1038/s41467-025-62353-1 · Cited by 10 · see citing works
A New Algebraic Approach for String Reconstruction from Substring Compositions
Gupta, U., & Mahdavifar, H. (2022) · IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit50566.2022.9834531 · Cited by 5 · see citing works
High density information storage through isotope ratio encoding
Sőregi, P., Zwillinger, M., Vágó, L., Csékei, M., & Kotschy, A. (2024) · Chemical Science · doi:10.1039/d4sc03519d · Cited by 5 · see citing works
Xu, X., Qin, W., Fu, H., Li, R., Chen, C., Sun, B., Pang, D., Shao, X., & Li, G. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.4c06292 · Cited by 5 · see citing works
Luo, B., Gao, S., Wu, M., Dong, X. W., Deng, X., & Hu, H. (2025) · Communications Materials · doi:10.1038/s43246-025-00915-y · Cited by 4 · see citing works
Wang, X., Wang, N., Zhou, P., Guo, R., Song, N., Zhang, Z., Yan, X., Yu, Z., & Li, G. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.5c02258 · Cited by 4 · see citing works
Park, H. M., Fargher, H. A., Song, K., Liu, H., Gu, Q., Lidskog, A., Dang, F., Makarov, D. E., & Anslyn, E. V. (2026) · Journal of the American Chemical Society · doi:10.1021/jacs.5c21819 · Cited by 3 · see citing works
A New Algebraic Approach for String Reconstruction From Substring Compositions
Gupta, U., & Mahdavifar, H. (2024) · IEEE Transactions on Information Theory · doi:10.1109/tit.2024.3493762 · Cited by 3 · see citing works
Hernández, A. U., Guyeux, C., Nicolaı̈, A., & Senet, P. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c06277 · Cited by 2 · see citing works
Lu, Y., Chen, S., Gao, S., Liu, H., Dong, X., Shen, W., & Ding, G. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356942 · Cited by 1 · see citing works
Modelling for Efficient Scientific Data Storage Using Simple Graphs in DNA
Usmani, A. R., & Wiese, L. (2024) · SN Computer Science · doi:10.1007/s42979-024-02672-0 · Cited by 1 · see citing works
Scaling Encodings to Larger Alphabets for Peptide-Based Data Storage
Hoppe, N., Specht, G., & Wiese, L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29912-3_28
Storing Data With Propargylic Amines Using Thin‐Layer Chromatography for the Data Retrieval
Mateus, M., Nallappan, S., & Rýček, L. (2026) · ChemPlusChem · doi:10.1002/cplu.70202
Data storage with amino acid sequences
Zhou, Y., Ng, C. C. A., & Yao, Z. (2026) · Trends in biotechnology · doi:10.1016/j.tibtech.2026.09.021
Self-citation
- Authors
- Ng, C. C. A., Tam, W. M., Yin, H., Wu, Q., So, P.-K., Wong, M. Y.-M., Lau, F. C. M., & Yao, Z.-P.
- Affiliations
- Hong Kong Polytechnic University (HK)
- Corresponding author
- Lau, Francis C. M.
- Yao, Zhong-Ping
- Venue
- Nature Communications
- Published
- 2021-07-13
- Volume
- 12
- Issue
- 1
- Pages
- 4242-4242
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8277807
- OpenAlex
- W3173530340
- Cited by
- 41
- References
- 41
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 8 · 2023: 6 · 2022: 11 · 2021: 1
- FWCI
- 2.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (81874306, 81601828)
- Jinan University
- Hong Kong Polytechnic University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Biological Computing
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Keywords
- peptide sequences, data storage density, error correction, address codes, tandem mass spectrometry, peptide synthesis, long-term data preservation
- MeSH terms
- Algorithms, Animals, Humans, Software, Databases, Protein, Proteomics
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
