The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
RNA Pseudoknot Prediction in Energy-Based Models
Abstract
RNA molecules are sequences of nucleotides that serve as more than mere intermediaries between DNA and proteins, e.g., as catalytic molecules. Computational prediction of RNA secondary structure is among the few structure prediction problems that can be solved satisfactorily in polynomial time. Most work has been done to predict structures that do not contain pseudoknots. Allowing pseudoknots introduces modeling and computational problems. In this paper we consider the problem of predicting RNA secondary structures with pseudoknots based on free energy minimization. We first give a brief comparison of energy-based methods for predicting RNA secondary structures with pseudoknots. We then prove that the general problem of predicting RNA secondary structures containing pseudoknots is NP complete for a large class of reasonable models of pseudoknots.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Moreover, predicting structures with pseudoknots is classified as an NP-complete problem [5].”
From Towards secondary structure prediction of longer mRNA sequences using a quantum-centric optimization scheme (2025) · cites this paper as [5]
Citations
Cites
Mathews, D. H., Sabina, J., Zuker, M., & Turner, D. H. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2700 · Cited by 3,795
Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information
Zuker, M., & Stiegler, P. (1981) · Nucleic Acids Research · doi:10.1093/nar/9.1.133 · Cited by 3,604
Improved Estimation of Secondary Structure in Ribonucleic Acids
Tinoco, I., Borer, P. N., Dengler, B., Levine, M., Uhlenbeck, O. C., Crothers, D. M., & Gralla, J. D. (1973) · Nature New Biology · doi:10.1038/newbio246040a0 · Cited by 2,270
Gilbert, W. (1986) · Nature · Cited by 1,941
Simple Fast Algorithms for the Editing Distance between Trees and Related Problems
Zhang, K., & Shasha, D. E. (1989) · SIAM Journal on Computing · doi:10.1137/0218082 · Cited by 1,312
The equilibrium partition function and base pair binding probabilities for RNA secondary structure
McCaskill, J. S. (1990) · Biopolymers · doi:10.1002/bip.360290621 · Cited by 1,288
A linear space algorithm for computing maximal common subsequences
Hirschberg, D. S. (1975) · Communications of the ACM · doi:10.1145/360825.360861 · Cited by 1,110
RNA sequence analysis using covariance models
Eddy, S. R., & Durbin, R. M. (1994) · Nucleic Acids Research · doi:10.1093/nar/22.11.2079 · Cited by 791
Rivas, E., & Eddy, S. R. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2436 · Cited by 763
Estimation of Secondary Structure in Ribonucleic Acids
Tinoco, I., Uhlenbeck, O. C., & Levine, M. (1971) · Nature · doi:10.1038/230362a0 · Cited by 686
Research works printed but not linked: 1
- Searls D.B., 1992, American Scientist, 80, 579
Cited by
Sorted by citations
Items 201–300 of 359
Delta: A Toolset for the Structural Analysis of Biological Sequences on a 3D Triangular Lattice
Jiang, M., Mayne, M., & Gillespie, J. (2007) · Springer eBooks · doi:10.1007/978-3-540-72031-7_47 · Cited by 5
A New Pseudoknots Folding Algorithm for RNA Structure Prediction
Li, H., & Zhu, D. (2005) · Lecture notes in computer science · doi:10.1007/11533719_12 · Cited by 5
On the combinatorics of sparsification
Huang, F. W. D., & Reidys, C. M. (2012) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-7-28 · Cited by 5
RNA Pseudoknot Prediction Using Term Rewriting
Fu, X. Z., Wang, H., Harrison, W., & Harrison, R. W. (2006) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2005.50 · Cited by 5
Tsang, H. H. (2007) · Summit (Simon Fraser University) · Cited by 5
Prediction de structures secondaires d'ARN avec pseudo-noeuds
Bon, M. (2009) · OpenGrey (Institut de l'Information Scientifique et Technique) · Cited by 5
Lengauer, T., Albrecht, M., & Domingues, F. S. (2012) · Wiley-VCH eBooks · doi:10.1002/3527600906.mcb.200400023.pub2 · Cited by 5
Modified free energy model to improve RNA secondary structure prediction with pseudoknots
Tong, K.-K., Cheung, K.-Y., Lee, K.-H., & Leung, K. (2013) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2013.6701532 · Cited by 4
Concepts and Introduction to RNA Bioinformatics
Gorodkin, J., Hofacker, I. L., & Ruzzo, W. L. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-709-9_1 · Cited by 4
Rubi, R. D., & Arockiam, L. (2012) · IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) · doi:10.1109/iccic.2012.6510271 · Cited by 4
K-Partite RNA Secondary Structures
Jiang, M., Tejada, P. J., Lasisi, R. O., Cheng, S., & Fechser, D. S. (2010) · Journal of Computational Biology · doi:10.1089/cmb.2009.0119 · Cited by 4
Licon, A., Taufer, M., Leung, M.-Y., & Johnson, K. L. (2010) · PubMed · Cited by 4
Shapes of topological RNA structures
Huang, F. W. D., & Reidys, C. M. (2015) · Mathematical Biosciences · doi:10.1016/j.mbs.2015.10.004 · Cited by 4
Prediction of RNA secondary structures with pseudoknots
Bon, M., & Orland, H. (2010) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2010.02.046 · Cited by 4
An RNA folding algorithm including pseudoknots based on dynamic weighted matching
Liu, H., Xu, D., Shao, J., & Wang, Y. (2005) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2005.10.001 · Cited by 4
Stacks in canonical RNA pseudoknot structures
Han, H. S. W., & Reidys, C. M. (2009) · Mathematical Biosciences · doi:10.1016/j.mbs.2008.12.011 · Cited by 4
Vialette, S. (2016) · Encyclopedia of Algorithms · doi:10.1007/978-1-4939-2864-4_445 · Cited by 4
An Earley-style Parser for Solving the RNA-RNA Interaction Problem
Wild, S. (2011) · Cited by 4
Partial chord diagrams and matrix modelsPreprint
Andersen, J. E., Fuji, H., Manabe, M., Penner, R., & Sułkowski, P. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.05840 · Cited by 5
Gong, T., Ju, F., & Bu, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.19.508461 · Cited by 4
RNA secondary structure prediction including pseudoknots
Beyer, W. (2010) · University of Vienna · doi:10.25365/thesis.11587 · Cited by 4
A rule-based approach for RNA pseudoknot prediction
Fu, X. Z., Wang, H., Harrison, R. W., & Harrison, W. L. (2008) · International Journal of Data Mining and Bioinformatics · doi:10.1504/ijdmb.2008.016757 · Cited by 3
Protein Modelling and Surface Folding by Limiting the Degrees of Freedom
Israelowitz, M., Weyand, B., Rizvi, S. W. H., Gille, C., & von Schroeder, H. P. (2012) · Studies in mechanobiology, tissue engineering and biomaterials · doi:10.1007/8415_2012_141 · Cited by 3
RNA Molecules: Glimpses Through an Algorithmic Lens
Condon, A. (2006) · Lecture notes in computer science · doi:10.1007/11682462_2 · Cited by 3
Kim, H., & Pirrung, M. C. (2002) · Journal of the American Chemical Society · doi:10.1021/ja012102a · Cited by 3
Memory efficient alignment between RNA sequences and stochastic grammar models of pseudoknots
Song, Y., Liu, C., Malmberg, R. L., He, C., & Cai, L. (2006) · International Journal of Bioinformatics Research and Applications · doi:10.1504/ijbra.2006.010606 · Cited by 3
RNA secondary structure prediction using a self‐consistent mean field approach
Kleesiek, J., & Torda, A. E. (2009) · Journal of Computational Chemistry · doi:10.1002/jcc.21398 · Cited by 3
Zhou, A., Jiang, H., Guo, J., & Zhu, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-71150-8_7 · Cited by 3
Reidys, C. M. (2010) · Springer eBooks · doi:10.1007/978-0-387-76731-4_5 · Cited by 3
Uses and abuses of intersected languages
Chiang, D. (2004) · Cited by 3
Exploring Secondary Structure Predictions for RNA-Targeted Drug Discovery: Power and Challenges
Zhang, Z., Dolcetti, G., Tyrchan, C., Maria, L. D., Bussi, G., & Czechtizky, W. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00108 · Cited by 2
Multiscale Graph-Theoretic Modeling of Biomolecular Structures
Jungck, J. R., Knisley, D. J., Pangborn, G. M., Riehl, M., & Wiesner, E. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-814066-6.00001-5 · Cited by 2
A graphical criterion of planarity for RNA secondary structures with pseudoknots in Rivas–Eddy class
Gao, S., & Ding, K. (2007) · Theoretical Computer Science · doi:10.1016/j.tcs.2007.09.026 · Cited by 2
An Efficient Algorithm for Upper Bound on the Partition Function of Nucleic Acids
Chitsaz, H., Forouzmand, E., & Haffari, G. (2013) · Journal of Computational Biology · doi:10.1089/cmb.2013.0003 · Cited by 2
Learning the Parameters of Stochastic Grammar Models for RNA Structures with Pseudoknots
Zhao, J., Cai, L., & Malmberg, R. L. (2006) · IEEE International Conference on Granular Computing (GrC) · doi:10.1109/grc.2006.1635778 · Cited by 2
A permutation based simulated annealing algorithm to predict pseudoknotted RNA secondary structures
Tsang, H. H., & Wiese, K. C. (2015) · International Journal of Bioinformatics Research and Applications · doi:10.1504/ijbra.2015.071938 · Cited by 2
Lengauer, T., & Hartmann, C. J. (2007) · Elsevier eBooks · doi:10.1016/b0-08-045044-x/00088-2 · Cited by 3
Zhou, A., Jiang, H., Guo, J., Feng, H., Liu, N., & Zhu, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-62389-4_48 · Cited by 2
Diverse RNA pseudoknots exist for short stems only
Baulin, E. F., Korinevskaya, A., Tikhonova, P., & Абрамович, Р. М. (2018) · Mathematical Biology and Bioinformatics · doi:10.17537/2018.13.533 · Cited by 1
Miklós, I. (2010) · Methods in molecular biology · doi:10.1007/978-1-60761-842-3_2 · Cited by 2
An iterative loop matching approach to the prediction of RNA secondary structures with pseudoknots
Ruan, J., Stormo, G. D., & Zhang, W. (2004) · IEEE Computational Systems Bioinformatics Conference (CSB) · doi:10.1109/csb.2003.1227394 · Cited by 2
RNA Pseudoknot Folding through Inference and Identification Using TAGRNA
Seesi, S. A., Rajasekaran, S., & Ammar, R. A. A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-00727-9_11 · Cited by 2
An Earley-style Parser for Solving the RNA-RNA Interaction Problem (Bachelor Thesis)
Wild, S. (2010) · Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology) · Cited by 2
Vialette, S. (2008) · Encyclopedia of Algorithms · doi:10.1007/978-0-387-30162-4_445 · Cited by 2
Kisses, ambivalent models and more: Contributions to the analysis of RNA secondary structure.
Janssen, S. (2014) · PUB – Publications at Bielefeld University (Bielefeld University) · doi:10.13140/2.1.1096.3846 · Cited by 2
Dawson, W., & Kawai, G. (2015) · Journal of Nucleic Acids Investigation · doi:10.4081/jnai.2015.2653 · Cited by 1
Chen, X., He, S., Bu, D., Chen, R., & Gao, W. (2007) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2007.4375595 · Cited by 1
Song, Y., Liu, C., & Li, Y. (2015) · The Computer Journal · doi:10.1093/comjnl/bxv043 · Cited by 1
Accuracy of RNA Structure Prediction Depends on the Pseudoknot Grammar
Eggers, D., zu Siederdissen, C. H., & Stadler, P. F. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-21175-1_3 · Cited by 1
Self-Playing RNA Inverse Folding
Obonyo, S., Jouandeau, N., & Owuor, D. O. (2024) · SN Computer Science · doi:10.1007/s42979-024-02659-x · Cited by 1
Predicting RNA Secondary Structures: One-grammar-fits-all Solution
Li, M., Cheng, M., Ye, Y., Hon, W.-K., Ting, H., Lam, T., Tang, C., Wong, T. K. F., & Yiu, S. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-19048-8_18 · Cited by 1
2-Dimensional HP Foldings of Dermaseptin-J2
Yan, S., & Wu, G. (2013) · Engineering · doi:10.4236/eng.2013.510b016 · Cited by 1
Prediction of Conserved and Consensus RNA Structures
Witwer, C. (2003) · Cited by 1
K-Partite RNA Secondary Structures
Jiang, M., Tejada, P. J., Lasisi, R. O., Cheng, S., & Fechser, D. S. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04241-6_14 · Cited by 1
Reeder, J. (2007) · PUB – Publications at Bielefeld University (Bielefeld University) · Cited by 1
An Introduction to RNA Structure and Pseudoknot Prediction
Sperschneider, J., & Datta, A. (2010) · Wiley eBooks · doi:10.1002/9780470892107.ch24 · Cited by 1
Fast Algorithm for Pseudoknotted RNA Structure Prediction
Li, H. (2010) · Journal of Computers · doi:10.4304/jcp.5.7.1100-1104 · Cited by 1
Heuristic Algorithm for Pseudoknotted RNA Structure Prediction
Li, H. (2008) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2008.676 · Cited by 1
Hofacker, I. L., & Stadler, P. F. (2007) · Springer eBooks · doi:10.1007/978-0-387-33532-2_8 · Cited by 1
A Seeded Genetic Algorithm for RNA Secondary Structural Prediction with Pseudoknots
Pham, R. (2008) · doi:10.31979/etd.tn97-fmrj · Cited by 1
The role of pre-mRNA secondary structure in gene splicing in Saccharomyces cerevisiae
Rogić, S. (2010) · cIRcle (University of British Columbia) · doi:10.14288/1.0051317 · Cited by 1
Profiling and Searching for RNA Pseudoknot Structures in Genomes
Liu, C., Song, Y., Malmberg, R. L., & Cai, L. (2005) · Lecture notes in computer science · doi:10.1007/11567752_2 · Cited by 1
Kumar, V., Alevras, D., Metkar, M., Welling, E., Cade, C., Niesen, I., Friedhoff, T., Park, J.-E., Shivpuje, S., LaDue, M., et al. (2025) · arXiv · doi:10.48550/arxiv.2505.05782 · Cited by 3
“Moreover, predicting structures with pseudoknots is classified as an NP-complete problem [5].”
Math 8803/4803, Spring 2008: Discrete Mathematical Biology
Heitsch, C. (2008)
RNA Secondary Structure Prediction Including Pseudoknots
Lyngsø, R. B. (2008) · Encyclopedia of Algorithms · doi:10.1007/978-0-387-30162-4_346
Self-citationInformatics (Computational Biology)
Lengauer, T. (2004) · Wiley-VCH eBooks · doi:10.1002/3527600906.mcb.200400023
Novel Algorithms for Structural Alignment of Non-coding RNAs
Kolbe, D. L. (2010) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7cr5rc5
RNA in Formation : Computational Studies on RNA Structure and Evolution
Smit, S. (2008) · Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam)
Radiocoloring in Planar Graphs
Papadopoulou, V. G. (2008) · Encyclopedia of Algorithms · doi:10.1007/978-0-387-30162-4_320
The Expected Order of Saturated RNA Secondary Structures
Jin, E. Y., & Nebel, M. E. (2012) · Workshop on Analytic Algorithmics and Combinatorics (ANALCO) · doi:10.1137/1.9781611973020.11
Counting RNA pseudoknotted structures (extended abstract)
Saule, C., Régnier, M., Steyaert, J., & Denise, A. (2010) · Discrete Mathematics & Theoretical Computer Science · doi:10.46298/dmtcs.2834
Classification of RNA sequences with pseudoknots using features based on partial sequences
Tong, K.-K., Cheung, K.-Y., Lee, K.-H., & Leung, K. (2015) · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · doi:10.1109/cibcb.2015.7300277
RNA secondary structure prediction algorithm based on steam-combination
Luo, J., & Chen, T. (2010) · Journal of Computer Applications · doi:10.3724/sp.j.1087.2010.01694 · Cited by 1
PreRkTAG: Prediction of RNA Knotted Structures Using Tree Adjoining Grammars
Dashti, H. T., Zare‐Mirakabad, F., Aghaeepour, N., Ahrabian, H., & Nowzari-Dalini, A. (2013) · Iranian Journal of Biotechnology · doi:10.5812/ijb.9213
Classification of coding and non-coding RNA in RNA-Seq data
Okada, H. M. (2011) · Summit (Simon Fraser University)
FINE-GRAINED PARALLEL APPLICATION SPECIFIC COMPUTING FOR RNA SECONDARY STRUCTURE PREDICTION ON FPGA
ZHU, Q., XIA, F., & JIN, G. (2014) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126614500315
Secondary Structure Models of Nucleic Acid Folding Kinetics
Sauerwine, B. (2011) · KiltHub Repository · doi:10.1184/r1/6721436
Uniform generation of RNA pseudoknot structures with genus filtrationPreprint
Huang, F. W. D., Nebel, M. E., & Reidys, C. M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1304.7397
Lei, J., Techa-Angkoon, P., Sun, Y., & Achawanantakun, R. (2013) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2506583.2506626
Xia, F., & Jin, G. (2014) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720014500085
A new heuristic method for approximating the number of local minima in partial RNA energy landscapes
Albrecht, A. A., Day, L., Souki, O. A. E., & Steinhöfel, K. K. (2015) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2015.11.002
Computational methods for RNA-RNA interaction prediction
Salari, R. (2010) · Summit (Simon Fraser University)
RNA Secondary Structure Prediction Using Hierarchical Folding
Jabbari, H., & Jabbari, C. H. (2007)
Identification and analysis of non-coding RNAs in large scale genomic data
Achawanantakun, R. (2014) · Michigan State University Libraries · doi:10.25335/m5j43j
Yildirim, I. (2008) · UR Research (University of Rochester)
Constraint Programming and Biology: RNA secondary structure
Agostino Dovier, A. (2012)
2-Dimensional HP Folding Structures of Caerin
王, 何. (2012) · Hans Journal of Computational Biology · doi:10.12677/hjcb.2012.24004
Towards a Shape Language for Interpreting RNA Folding
Mamuye, A. L., Merelli, E., & Tesei, L. (2016) · International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS) · doi:10.4108/eai.3-12-2015.2262523
Linear Time Algorithm for Parsing RNA Secondary Structure Extended Abstract
Rastegari, B., & Condon, A. (2005)
Exploring Life through Logic Programming
A, D. P., Agostino Dovier, A., Formisano, A., & Pontelli, E. (2015)
Pseudoknots in RNA folding landscapes SUPPLEMENTAL MATERIAL
Hofacker, I. L., & Stadler, P. F. (2015)
Parametric RNA Partition Function Algorithms
Ding, Y. (2010)
Akiyama, M., Sakakibara, Y., & Sato, K. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/303172
Computational Design and Experimental Validation of Functional Ribonucleic Acid Nanostructures
Zandi, K. (2018) · Spectrum Research Repository (Concordia University)
Maximum Stacking Base Pairs: Hardness and Approximation by Nonlinear LP-Rounding
Liu, L., Jiang, H., Liu, P., Zhu, B., & Zhu, D. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-20242-2_21
On the combinatorics of sparsificationPreprint
Huang, F. W. D., & Reidys, C. M. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1201.0308
Inverse Folding of RNA Pseudoknot StructuresPreprint
Gao, J., Li, L. Y. M., & Reidys, C. M. (2009) · arXiv (Cornell University) · doi:10.48550/arxiv.0905.0733
Combinatorial Analysis for Pseudoknot RNA with Complex StructurePreprint
Zhao, Y. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.06871
Maximum Stacking Base Pairs: Hardness and Approximation by Nonlinear Linear Programming-Rounding
Liu, L., Jiang, H., Liu, P., Zhu, B., & Zhu, D. (2020) · Journal of Computational Biology · doi:10.1089/cmb.2019.0288
Metadata
- Authors
- Lyngsø, R. B., & Pedersen, C. N. S.
- Affiliations
- University of California, Santa Cruz (US)
- Aarhus University (DK)
- Venue
- Journal of Computational Biology
- Publisher
- SAGE Publications
- Published
- 2000-08
- Volume
- 7
- Issue
- 3-4
- Pages
- 409-427
- ISSN
- 1066-5277 (ISSN-L)
- 1557-8666
- OpenAlex
- W2076756368
- Cited by
- 359
- References
- 28
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 25 · 2023: 8 · 2022: 27 · 2021: 9 · 2020: 8 · 2019: 9 · 2018: 11 · 2017: 10 · 2016: 11 · 2015: 13 · 2014: 11 · 2013: 16 · 2012: 21
- FWCI
- 1.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computational Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Physical Sciences › Mathematics › Theoretical Computer Science › DNA and Biological Computing
- Keywords
- RNA pseudoknots, RNA secondary structure prediction, energy-based models, free energy minimization, NP-completeness, computational complexity
- MeSH terms
- Algorithms, Models, Molecular, Nucleic Acid Conformation, RNA, Thermodynamics, Computational Biology
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
