Cited by 51Ion Channels and ReceptorsProtein Structure and DynamicsIon channel regulation and function

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Crosstalk between regulatory elements in disordered TRPV4 N-terminus modulates lipid-dependent channel activity

Open access

Published version of a preprint

Abstract

Intrinsically disordered regions (IDRs) are essential for membrane receptor regulation but often remain unresolved in structural studies. TRPV4, a member of the TRP vanilloid channel family involved in thermo- and osmosensation, has a large N-terminal IDR of approximately 150 amino acids. With an integrated structural biology approach, we analyze the structural ensemble of the TRPV4 IDR and the network of antagonistic regulatory elements it encodes. These modulate channel activity in a hierarchical lipid-dependent manner through transient long-range interactions. A highly conserved autoinhibitory patch acts as a master regulator by competing with PIP 2 binding to attenuate channel activity. Molecular dynamics simulations show that loss of the interaction between the PIP 2 -binding site and the membrane reduces the force exerted by the IDR on the structured core of TRPV4. This work demonstrates that IDR structural dynamics are coupled to TRPV4 activity and highlights the importance of IDRs for TRP channel function and 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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-023-39808-4

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Flagged first, then by citations

Research works printed but not linked: 91

  1. Verkest, C. et al. Intrinsically disordered intracellular domains control key features of the mechanically-gated ion channel PIEZO2. Nat. Commun. 13, 1365 (2022). · DOI
  2. Magidovich, E., Orr, I., Fass, D., Abdu, U. & Yifrach, O. Intrinsic disorder in the C-terminal domain of the Shaker voltage-activated K+ channel modulates its interaction with scaffold proteins. Proc. Natl Acad. Sci. USA 104, 13022–13027 (2007). · DOI
  3. Warnet, X. L., Bakke Krog, H., Sevillano-Quispe, O. G., Poulsen, H. & Kjaergaard, M. The C-terminal domains of the NMDA receptor: how intrinsically disordered tails affect signalling, plasticity and disease. Eur. J. Neurosci. 54, 6713–6739 (2021). · DOI · Paper page
  4. Goretzki, B., Guhl, C., Tebbe, F., Harder, J.-M. & Hellmich, U. A. Unstructural biology of TRP ion channels: the role of intrinsically disordered regions in channel function and regulation. J. Mol. Biol. 433, 166931 (2021). · DOI
  5. Goretzki, B., Tebbe, F., Mitrovic, S.-A. & Hellmich, U. A. Backbone NMR assignments of the extensive human and chicken TRPV4 N-terminal intrinsically disordered regions as important players in ion channel regulation. Biomol. NMR Assign. 16, 205–212 (2022). · DOI
  6. Wiedemann, C. et al. Extent of intrinsic disorder and NMR chemical shift assignments of the distal N-termini from human TRPV1, TRPV2 and TRPV3 ion channels. Biomol. NMR Assign. 16, 289–296 (2022). · DOI
  7. Garcia-Elias, A. et al. The TRPV4 Channel. in Mammalian Transient Receptor Potential (TRP) Cation Channels: Volume I (eds. Nilius, B. & Flockerzi, V.) 293–319 (Springer, 2014)https://doi.org/10.1007/978-3-642-54215-2_12. · DOI
  8. Toft-Bertelsen, T. L. & MacAulay, N. TRPing to the point of clarity: understanding the function of the complex TRPV4 ion channel. Cells 10, 165 (2021). · DOI
  9. Taga, A. et al. TRPV4 mutations causing mixed neuropathy and skeletal phenotypes result in severe gain of function. Ann. Clin. Transl. Neurol. 9, 375–391 (2022). · DOI
  10. Landouré, G. et al. Mutations in TRPV4 cause Charcot-Marie-Tooth disease type 2C. Nat. Genet 42, 170–174 (2010). · DOI
  11. Deng, H.-X. et al. Scapuloperoneal spinal muscular atrophy and CMT2C are allelic disorders caused by alterations in TRPV4. Nat. Genet. 42, 165–169 (2010). · DOI
  12. Rock, M. J. et al. Gain-of-function mutations in TRPV4 cause autosomal dominant brachyolmia. Nat. Genet. 40, 999–1003 (2008). · DOI
  13. Auer-Grumbach, M. et al. Alterations in the ankyrin domain of TRPV4 cause congenital distal SMA, scapuloperoneal SMA and HMSN2C. Nat. Genet. 42, 160–164 (2010). · DOI
  14. Doñate-Macián, P. et al. The TRPV4 channel links calcium influx to DDX3X activity and viral infectivity. Nat. Commun. 9, 2307 (2018). · DOI
  15. Bera, K. et al. Extracellular fluid viscosity enhances cell migration and cancer dissemination. Nature 611, 365–373 (2022). · DOI
  16. Alpizar, Y. A. et al. TRPV4 activation triggers protective responses to bacterial lipopolysaccharides in airway epithelial cells. Nat. Commun. 8, 1059 (2017). · DOI
  17. Inada, H., Procko, E., Sotomayor, M. & Gaudet, R. Structural and biochemical consequences of disease-causing mutations in the ankyrin repeat domain of the human TRPV4 channel. Biochemistry 51, 6195–6206 (2012). · DOI
  18. Hellmich, U. A. & Gaudet, R. Structural biology of TRP channels. in Mammalian Transient Receptor Potential (TRP) Cation Channels: Volume II (eds. Nilius, B. & Flockerzi, V.) 963–990 (Springer International Publishing, 2014). https://doi.org/10.1007/978-3-319-05161-1_10. · DOI
  19. Deng, Z. et al. Cryo-EM and X-ray structures of TRPV4 reveal insight into ion permeation and gating mechanisms. Nat. Struct. Mol. Biol. 25, 252–260 (2018). · DOI
  20. Botte, M. et al. Cryo-EM structural studies of the agonist complexed human TRPV4 ion-channel reveals novel structural rearrangements resulting in an open-conformation. 2020.10.13.334797 Preprint at https://doi.org/10.1101/2020.10.13.334797 (2020). · DOI
  21. Kwon, D.H., Zhang, F. et al. TRPV4-Rho GTPase complex structures reveal mechanisms of gating and disease. Nat Commun 14, 3732 (2023). · DOI
  22. Nadezhdin, K.D. et al. Structure of human TRPV4 in complex with GTPase RhoA. Nat Commun 14, 3733 (2023). · DOI
  23. Singh, A. K. et al. Structural basis of temperature sensation by the TRP channel TRPV3. Nat. Struct. Mol. Biol. 26, 994–998 (2019). · DOI
  24. Pumroy, R. A. et al. Structural insights into TRPV2 activation by small molecules. Nat. Commun. 13, 2334 (2022). · DOI
  25. Nadezhdin, K. D. et al. Structural mechanism of heat-induced opening of a temperature-sensitive TRP channel. Nat. Struct. Mol. Biol. 28, 564–572 (2021). · DOI
  26. Toft-Bertelsen, T. L. et al. Volume sensing in the transient receptor potential vanilloid 4 ion channel is cell type–specific and mediated by an N-terminal volume-sensing domain. J. Biol. Chem. 294, 18421–18434 (2019). · DOI
  27. Liedtke, W., Tobin, D. M., Bargmann, C. I. & Friedman, J. M. Mammalian TRPV4 (VR-OAC) directs behavioral responses to osmotic and mechanical stimuli in Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 100, 14531–14536 (2003). · DOI
  28. Goswami, R. et al. Mechanosensing by TRPV4 mediates stiffness-induced foreign body response and giant cell formation. Sci. Signal. 14, eabd4077 (2021). · DOI
  29. Goretzki, B. et al. Structural basis of TRPV4 N terminus interaction with syndapin/PACSIN1-3 and PIP2. Structure 26, 1583–1593.e5 (2018). · DOI
  30. Cuajungco, M. P. et al. PACSINs bind to the TRPV4 cation channel: PACSIN 3 modulates the subcellular localization of TRPV4 *. J. Biol. Chem. 281, 18753–18762 (2006). · DOI
  31. McCray, B. A. et al. Neuropathy-causing TRPV4 mutations disrupt TRPV4-RhoA interactions and impair neurite extension. Nat. Commun. 12, 1444 (2021). · DOI · Paper page
  32. D’hoedt, D. et al. Stimulus-specific modulation of the cation channel TRPV4 by PACSIN 3 *. J. Biol. Chem. 283, 6272–6280 (2008). · DOI
  33. Garcia-Elias, A. et al. Phosphatidylinositol-4,5-biphosphate-dependent rearrangement of TRPV4 cytosolic tails enables channel activation by physiological stimuli. Proc. Natl Acad. Sci. USA 110, 9553–9558 (2013). · DOI
  34. Wills, R. C. & Hammond, G. R. V. PI(4,5)P2: signaling the plasma membrane. Biochem. J. 479, 2311–2325 (2022). · DOI
  35. Hille, B., Dickson, E. J., Kruse, M., Vivas, O. & Suh, B.-C. Phosphoinositides regulate ion channels. Biochim. Biophys. Acta 1851, 844–856 (2015). · DOI · Paper page
  36. Rout, M. P. & Sali, A. Principles for integrative structural biology studies. Cell 177, 1384–1403 (2019). · DOI
  37. Bernadó, P., Mylonas, E., Petoukhov, M. V., Blackledge, M. & Svergun, D. I. Structural characterization of flexible proteins using small-angle X-ray scattering. J. Am. Chem. Soc. 129, 5656–5664 (2007). · DOI
  38. Tria, G., Mertens, H. D. T., Kachala, M. & Svergun, D. I. Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering. IUCrJ 2, 207–217 (2015). · DOI
  39. Masson, G. R. et al. Recommendations for performing, interpreting and reporting hydrogen deuterium exchange mass spectrometry (HDX-MS) experiments. Nat. Methods 16, 595–602 (2019). · DOI
  40. Merkley, E. D. et al. Distance restraints from crosslinking mass spectrometry: mining a molecular dynamics simulation database to evaluate lysine–lysine distances. Protein Sci. 23, 747–759 (2014). · DOI
  41. Thorneloe, K. S. et al. N-((1S)−1-{[4-((2S)−2-{[(2,4-Dichlorophenyl)sulfonyl]amino}−3-hydroxypropanoyl)−1-piperazinyl]carbonyl}−3-methylbutyl)−1-benzothiophene-2-carboxamide (GSK1016790A), a Novel and Potent Transient Receptor Potential Vanilloid 4 Channel Agonist Induces Urinary Bladder Contraction and Hyperactivity: Part I. J Pharmacol Exp Ther 326, 432–442 (2008). · DOI
  42. Takahashi, N. et al. TRPV4 channel activity is modulated by direct interaction of the ankyrin domain to PI(4,5)P2. Nat. Commun. 5, 4994 (2014).
  43. Harraz, O. F., Longden, T. A., Hill-Eubanks, D. & Nelson, M. T. PIP2 depletion promotes TRPV4 channel activity in mouse brain capillary endothelial cells. eLife 7, e38689 (2018). · DOI · Paper page
  44. Caires, R. et al. Genetic- and diet-induced ω−3 fatty acid enrichment enhances TRPV4-mediated vasodilation in mice. Cell Rep. 40, 111306 (2022). · DOI
  45. Müller, D. J., Helenius, J., Alsteens, D. & Dufrêne, Y. F. Force probing surfaces of living cells to molecular resolution. Nat. Chem. Biol. 5, 383–390 (2009). · DOI
  46. VanBuren, P., Guilford, W. H., Kennedy, G., Wu, J. & Warshaw, D. M. Smooth muscle myosin: a high force-generating molecular motor. Biophys. J. 68, 256S–259S (1995).
  47. Phelps, C. B., Wang, R. R., Choo, S. S. & Gaudet, R. Differential regulation of TRPV1, TRPV3, and TRPV4 sensitivity through a conserved binding site on the ankyrin repeat domain *. J. Biol. Chem. 285, 731–740 (2010). · DOI
  48. Aisenberg, W. H. et al. Multiubiquitination of TRPV4 reduces channel activity independent of surface localization. J. Biol. Chem. 298, 101826 (2022). · DOI
  49. Arniges, M., Fernández-Fernández, J. M., Albrecht, N., Schaefer, M. & Valverde, M. A. Human TRPV4 channel splice variants revealed a key role of ankyrin domains in multimerization and trafficking. J. Biol. Chem. 281, 1580–1586 (2006). · DOI
  50. Ashkenazy, H. et al. ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Res. 44, W344–W350 (2016). · DOI · Paper page
  51. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012). · DOI · Paper page
  52. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009). · DOI
  53. Azatian, S. B., Kaur, N. & Latham, M. P. Increasing the buffering capacity of minimal media leads to higher protein yield. J. Biomol. NMR 73, 11–17 (2019). · DOI
  54. La Verde, V., Dominici, P. & Astegno, A. Determination of hydrodynamic radius of proteins by size exclusion chromatography. Bio Protoc. 7, e2230 (2017). · DOI
  55. Zimm, B. H. The scattering of light and the radial distribution function of high polymer solutions. J. Chem. Phys. 16, 1093–1099 (1948). · DOI
  56. Zhao, H., Brown, P. H. & Schuck, P. On the distribution of protein refractive index increments. Biophys. J. 100, 2309–2317 (2011). · DOI
  57. The Proteomics Protocols Handbook. (Humana Press, 2005). https://doi.org/10.1385/1592598900. · DOI
  58. Kelly, S. M., Jess, T. J. & Price, N. C. How to study proteins by circular dichroism. Biochim. Biophys. Acta (BBA) 1751, 119–139 (2005). · DOI
  59. Blanchet, C. E. et al. Versatile sample environments and automation for biological solution X-ray scattering experiments at the P12 beamline (PETRA III, DESY). J. Appl Cryst. 48, 431–443 (2015). · DOI
  60. Graewert, M. A. et al. Adding size exclusion chromatography (SEC) and light scattering (LS) devices to obtain high-quality small angle X-ray scattering (SAXS) data. Crystals 10, 975 (2020). · DOI
  61. Hajizadeh, N. R., Franke, D. & Svergun, D. I. Integrated beamline control and data acquisition for small-angle X-ray scattering at the P12 BioSAXS beamline at PETRAIII storage ring DESY. J. Synchrotron Rad. 25, 906–914 (2018). · DOI
  62. Franke, D., Kikhney, A. G. & Svergun, D. I. Automated acquisition and analysis of small angle X-ray scattering data. Nucl. Instrum. Methods Phys. Res. Sect. A: Accelerators, Spectrometers, Detect. Associated Equip. 689, 52–59 (2012). · DOI
  63. Panjkovich, A. & Svergun, D. I. CHROMIXS: automatic and interactive analysis of chromatography-coupled small-angle X-ray scattering data. Bioinformatics 34, 1944–1946 (2018). · DOI
  64. Franke, D., Jeffries, C. M. & Svergun, D. I. Correlation Map, a goodness-of-fit test for one-dimensional X-ray scattering spectra. Nat. Methods 12, 419–422 (2015). · DOI
  65. Manalastas-Cantos, K. et al. ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis. J. Appl. Cryst. 54, 343–355 (2021). · DOI
  66. Guinier, A. La diffraction des rayons X aux très petits angles: application à l’étude de phénomènes ultramicroscopiques. Ann. Phys. 11, 161–237 (1939). · DOI
  67. Svergun, D. I. Determination of the regularization parameter in indirect-transform methods using perceptual criteria. J. Appl. Cryst. 25, 495–503 (1992). · DOI
  68. Hajizadeh, N. R., Franke, D., Jeffries, C. M. & Svergun, D. I. Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data. Sci. Rep. 8, 7204 (2018). · DOI
  69. Franke, D., Jeffries, C. M. & Svergun, D. I. Machine learning methods for X-ray scattering data analysis from biomacromolecular solutions. Biophys. J. 114, 2485–2492 (2018). · DOI
  70. Receveur-Brechot, V. & Durand, D. How random are intrinsically disordered proteins? A small angle scattering perspective. Curr. Protein Pept. Sci. 13, 55–75 (2012). · DOI
  71. Wales, T. E., Fadgen, K. E., Gerhardt, G. C. & Engen, J. R. High-speed and high-resolution UPLC separation at zero degrees celsius. Anal. Chem. 80, 6815–6820 (2008). · DOI
  72. Geromanos, S. J. et al. The detection, correlation, and comparison of peptide precursor and product ions from data independent LC-MS with data dependant LC-MS/MS. Proteomics 9, 1683–1695 (2009). · DOI
  73. Li, G.-Z. et al. Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics 9, 1696–1719 (2009). · DOI
  74. Leitner, A. et al. Expanding the chemical cross-linking toolbox by the use of multiple proteases and enrichment by size exclusion chromatography. Mol. Cell Proteom. 11, M111.014126 (2012). · DOI
  75. Leitner, A., Walzthoeni, T. & Aebersold, R. Lysine-specific chemical cross-linking of protein complexes and identification of cross-linking sites using LC-MS/MS and the xQuest/xProphet software pipeline. Nat. Protoc. 9, 120–137 (2014). · DOI
  76. Williamson, M. P. Chemical Shift Perturbation. in Modern Magnetic Resonance (ed. Webb, G. A.) 995–1012 (Springer International Publishing, 2018). https://doi.org/10.1007/978-3-319-28388-3_76. · DOI
  77. Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1, 19–25 (2015). · DOI · Paper page
  78. Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007). · DOI
  79. Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981). · DOI
  80. Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995). · DOI
  81. Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997). · DOI
  82. Robustelli, P., Piana, S. & Shaw, D. E. Developing a molecular dynamics force field for both folded and disordered protein states. Proc. Natl Acad. Sci. USA 115, E4758–E4766 (2018). · DOI
  83. Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. 29, 1859–1865 (2008). · DOI · Paper page
  84. Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2017). · DOI
  85. Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., DiNola, A. & Haak, J. R. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684–3690 (1984). · DOI
  86. Marrink, S. J., Risselada, H. J., Yefimov, S., Tieleman, D. P. & de Vries, A. H. The MARTINI force field: coarse grained model for biomolecular simulations. J. Phys. Chem. B 111, 7812–7824 (2007). · DOI
  87. Benayad, Z., von Bülow, S., Stelzl, L. S. & Hummer, G. Simulation of FUS protein condensates with an adapted coarse-grained model. J. Chem. Theory Comput. 17, 525–537 (2021). · DOI
  88. Thallmair, S., Javanainen, M., Fábián, B., Martinez-Seara, H. & Marrink, S. J. Nonconverged constraints cause artificial temperature gradients in lipid bilayer simulations. J. Phys. Chem. B 125, 9537–9546 (2021). · DOI
  89. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). · DOI · Paper page
  90. Perez-Riverol, Y. et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Res. 50, D543–D552 (2022). · DOI · Paper page
  91. Pearson, K. X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Lond. Edinb. Dublin Philos. Mag. J. Sci. 50, 157–175 (1900). · DOI

Metadata

Authors
Goretzki, B., Wiedemann, C., McCray, B. A., Schäfer, S. L., Jansen, J., Tebbe, F., Mitrovic, S.-A., Nöth, J., Cabezudo, A. C., Donohue, J. K., Jeffries, C. M., Steinchen, W., Stengel, F., Sumner, C. J., Hummer, G., & Hellmich, U. A.
Affiliations
  • Goethe University Frankfurt (DE)
  • Friedrich Schiller University Jena (DE)
  • Johns Hopkins University (US)
  • University of Konstanz (DE)
  • Johannes Gutenberg University Mainz (DE)
  • Max Planck Institute of Biophysics (DE)
  • European Molecular Biology Laboratory (DE)
  • Philipps University of Marburg (DE)
Corresponding author
Hellmich, Ute A.
Venue
Nature Communications
Published
2023-07-13
Volume
14
Issue
1
Pages
4165-4165
ISSN
2041-1723 (ISSN-L)
OpenAlex
W4384200955
Cited by
51
References
3
Citations by year
2026: 13 · 2025: 19 · 2024: 13 · 2023: 6
FWCI
9.41
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • KOPS (University of Konstanz) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Common Library Network (Der Gemeinsame Bibliotheksverbund) (submittedVersion, cc-by)
Funders
  • Muscular Dystrophy Association (629305)
  • European Commission
  • Deutsche Forschungsgemeinschaft (EXC 2051—, STE 2517/5-1, 390713860, 450648163, 324652314)
  • Max-Planck-Gesellschaft
  • National Institutes of Health
  • Deutsches Elektronen-Synchrotron (SAXS-1106)
  • European Regional Development Fund
  • National Institute of Neurological Disorders and Stroke (K08NS102509, NS102509, R35NS122306)
Topics
  • Life Sciences › Neuroscience › Sensory Systems › Ion Channels and Receptors
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
Keywords
TRPV4, intrinsically disordered regions, PIP2 binding, long-range interactions, structural ensembles, molecular dynamics simulation, channel deactivation
MeSH terms
Protein Domains, Cell Physiological Phenomena, Lipids, Regulatory Sequences, Nucleic Acid, TRPV Cation Channels

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