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Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy
Open accessAbstract
This is a review of bootstrap methods, concentrating on basic ideas and applications rather than theoretical considerations. It begins with an exposition of the bootstrap estimate of standard error for one-sample situations. Several examples, some involving quite complicated statistical procedures, are given. The bootstrap is then extended to other measures of statistical accuracy such as bias and prediction error, and to complicated data structures such as time series, censored data, and regression models. Several more examples are presented illustrating these ideas. The last third of the paper deals mainly with bootstrap confidence intervals.
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Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-4380-9_25 · Cited by 45,239
Regression Models and Life-Tables
Cox, D. R. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_37 · Cited by 26,297
Bootstrap methods: another look at the jackknife
Efron, B. (1979) · The Annals of Statistics · doi:10.1214/aos/1176344552 · Cited by 17,602
Self-citationAn Analysis of Transformations
Box, G. E. P., & Cox, D. R. (1964) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1964.tb00553.x · Cited by 15,287
Linear Statistical Inference and its Applications
Rao, C. R. (1973) · Wiley series in probability and statistics · doi:10.1002/9780470316436 · Cited by 10,474
Continuous Univariate Distributions.
Omori, Y., Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995) · Journal of the American Statistical Association · doi:10.2307/2291547 · Cited by 9,085
The Jackknife, the Bootstrap and Other Resampling Plans
Efron, B. (1982) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611970319 · Cited by 8,120
Self-citationLinear Statistical Inference and Its Applications.
Robertson, C., & Rao, C. R. (1975) · Biometrics · doi:10.2307/2529568 · Cited by 3,639
Better Bootstrap Confidence Intervals
Efron, B. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478410 · Cited by 3,462
Self-citationA leisurely look at the bootstrap, the jackknife, and cross-validation
Efron, B., & Gong, G. (1983) · The American Statistician · doi:10.1080/00031305.1983.10483087 · Cited by 3,229
Self-citation
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Petersen, M. A. (2008) · Review of Financial Studies · doi:10.1093/rfs/hhn053 · Cited by 10,804
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Altman, N. (1992) · The American Statistician · doi:10.1080/00031305.1992.10475879 · Cited by 5,657
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Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010) · Psychological Methods · doi:10.1037/a0020141 · Cited by 3,796
HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-Span, and Viral Generation Time
Perelson, A. S., Neumann, A. U., Markowitz, M. H., Leonard, J. M., & Ho, D. D. (1996) · Science · doi:10.1126/science.271.5255.1582 · Cited by 3,533
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962
Bracken, M. B., Shepard, M. J., Collins, W. F., Holford, T. R., Young, W., Baskin, D. S., Eisenberg, H. M., Flamm, E. S., Leo-Summers, L. S., Maroon, J. C., et al. (1990) · New England Journal of Medicine · doi:10.1056/nejm199005173222001 · Cited by 2,698
Estimating Standard Errors in Finance Panel Data Sets: Comparing ApproachesPreprint
Petersen, M. A. (2006) · SSRN Electronic Journal · doi:10.2139/ssrn.661481 · Cited by 2,561
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Künsch, H. R. (1989) · The Annals of Statistics · doi:10.1214/aos/1176347265 · Cited by 2,454
Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012) · Long Range Planning · doi:10.1016/j.lrp.2012.09.008 · Cited by 2,626
Simple technical trading rules and the stochastic properties of stock returns
BROCK, W., LAKONISHOK, J., & LeBARON, B. (1992) · The Journal of Finance · doi:10.1111/j.1540-6261.1992.tb04681.x · Cited by 2,301
Hepatitis C Viral Dynamics in Vivo and the Antiviral Efficacy of Interferon-α Therapy
Neumann, A. U., Lam, N. P., Dahari, H., Gretch, D. R., Wiley, T. E., Layden, T. J., & Perelson, A. S. (1998) · Science · doi:10.1126/science.282.5386.103 · Cited by 2,111
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Chang, C., & Glover, G. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.011 · Cited by 1,808
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Perelson, A. S., Essunger, P., Cao, Y., Vesanen, M., Hurley, A., Saksela, K., Markowitz, M. H., & Ho, D. D. (1997) · Nature · doi:10.1038/387188a0 · Cited by 1,861
High plant diversity is needed to maintain ecosystem services
Isbell, F., Calcagno, V., Hector, A., Connolly, J., Harpole, W. S., Reich, P. B., Scherer-Lorenzen, M., Schmid, B., Tilman, D., van Ruijven, J., et al. (2011) · Nature · doi:10.1038/nature10282 · Cited by 1,664
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Bollen, K. A., & Stine, R. (1990) · Sociological Methodology · doi:10.2307/271084 · Cited by 1,305
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Kerr, K. F., Martin, M., & Churchill, G. A. (2000) · Journal of Computational Biology · doi:10.1089/10665270050514954 · Cited by 1,310
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Bollen, K. A., & Stine, R. A. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002004 · Cited by 1,831
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Mohammadi, S. A., & Prasanna, B. M. (2003) · Crop Science · doi:10.2135/cropsci2003.1235 · Cited by 1,272
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Schluter, D. (1996) · Evolution · doi:10.1111/j.1558-5646.1996.tb03563.x · Cited by 1,269
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Efron, B., & Tibshirani, R. (1991) · Science · doi:10.1126/science.253.5018.390 · Cited by 1,192
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Using Degradation Measures to Estimate a Time-to-Failure Distribution
Lu, C. J., & Meeker, W. O. (1993) · Technometrics · doi:10.1080/00401706.1993.10485038 · Cited by 1,163
Biondi, F., & Waikul, K. K. (2004) · Computers & Geosciences · doi:10.1016/j.cageo.2003.11.004 · Cited by 1,131
Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results
Streukens, S., & Leroi-Werelds, S. (2016) · European Management Journal · doi:10.1016/j.emj.2016.06.003 · Cited by 1,120
Spatial Pattern Analysis of Functional Brain Images Using Partial Least Squares
McIntosh, A. R., Bookstein, F. L., Haxby, J. V., & Grady, C. L. (1996) · NeuroImage · doi:10.1006/nimg.1996.0016 · Cited by 1,095
Partial least squares analysis of neuroimaging data: applications and advances
McIntosh, A. R., & Lobaugh, N. J. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.020 · Cited by 1,084
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Goldman, N., Anderson, J. P., & Rodrigo, A. G. (2000) · Systematic Biology · doi:10.1080/106351500750049752 · Cited by 1,086
Slowing down as an early warning signal for abrupt climate change
Dakos, V., Scheffer, M., van Nes, E. H., Brovkin, V. A., Petoukhov, V. K., & Held, H. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0802430105 · Cited by 1,036
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Balogh, M. L., Morris, S. L., Yee, H. K. C., Carlberg, R. G., & Ellingson, E. (1999) · The Astrophysical Journal · doi:10.1086/308056 · Cited by 982
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Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babaï, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., et al. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 1,187
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Lytle, B. W., Blackstone, E. H., Loop, F. D., Houghtaling, P. L., Arnold, J. H., Akhrass, R., McCarthy, P. M., & Cosgrove, D. M. (1999) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/s0022-5223(99)70365-x · Cited by 920
Kamphorst, J. J., Nofal, M., Commisso, C., Hackett, S. R., Lu, W., Grabocka, E., Vander Heiden, M. G., Miller, G., Drebin, J. A., Bar-Sagi, D., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-14-2211 · Cited by 893
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Rillig, M. C., Ryo, M., Lehmann, A., Aguilar‐Trigueros, C. A., Buchert, S., Wulf, A., Iwasaki, A., Roy, J., & Yang, G. (2019) · Science · doi:10.1126/science.aay2832 · Cited by 932
Mould, D., & Upton, R. N. (2013) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1038/psp.2013.14 · Cited by 906
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Preacher, K. J., Zhang, Z., & Zyphur, M. J. (2011) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2011.557329 · Cited by 889
Li, J., Zhang, Z., Rosenzweig, J. M., Wang, Y. Y., & Chan, D. W. (2002) · Clinical Chemistry · doi:10.1093/clinchem/48.8.1296 · Cited by 885
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Walther, B. A., & Moore, J. L. (2005) · Ecography · doi:10.1111/j.2005.0906-7590.04112.x · Cited by 849
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Hudson, J. J., Kara, D. M., Smallman, I. J., Sauer, B. E., Tarbutt, M. R., & Hinds, E. A. (2011) · Nature · doi:10.1038/nature10104 · Cited by 748
Impairment in movement skills of children with autistic spectrum disorders
Green, D., Charman, T., Pickles, A. R., Chandler, S., Loucas, T., Simonoff, E. A., & Baird, G. (2009) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2008.03242.x · Cited by 749
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Michael, A. J. (1987) · Journal of Geophysical Research Atmospheres · doi:10.1029/jb092ib01p00357 · Cited by 740
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Efron, B., & Tibshirani, R. (1995) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.2307/2983304 · Cited by 22,453
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Harris, N. L., Brown, S., Hagen, S. C., Saatchi, S. S., Petrova, S., Salas, W., Hansen, M. C., Potapov, P. V., & Lotsch, A. (2012) · Science · doi:10.1126/science.1217962 · Cited by 755
Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology
Haak, D. C., HilleRisLambers, J., Pitre, E., & Freeman, S. (2011) · Science · doi:10.1126/science.1204820 · Cited by 959
Spreng, R. N., Sepulcre, J., Turner, G. R., Stevens, W. D., & Schacter, D. L. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00281 · Cited by 668
McLachlan, G. J. (1987) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347790 · Cited by 709
Machine learning and radiology
Wang, S., & Summers, R. M. (2012) · Medical Image Analysis · doi:10.1016/j.media.2012.02.005 · Cited by 727
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Bresnan, J. W., Cueni, A., Nikitina, T. V., & Baayen, R. H. (2007) · Max Planck Digital Library · Cited by 696
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Brenning, A. (2005) · Natural hazards and earth system sciences · doi:10.5194/nhess-5-853-2005 · Cited by 698
Degree 12 model of shear velocity heterogeneity in the mantle
Su, W., Woodward, R. L., & Dziewoński, A. M. (1994) · Journal of Geophysical Research Atmospheres · doi:10.1029/93jb03408 · Cited by 672
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HALL, P., Horowitz, J. L., & Jing, B. (1995) · Biometrika · doi:10.1093/biomet/82.3.561 · Cited by 647
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Jablonka, K. M., Ongari, D., Moosavi, S. M., & Smit, B. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00004 · Cited by 656
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Sauerbrei, W., & Schumacher, M. (1992) · Statistics in Medicine · doi:10.1002/sim.4780111607 · Cited by 601
Buerger, K., Ewers, M., Pirttila, T., Zinkowski, R., Alafuzoff, I., Teipel, S. J., DeBernardis, J., Kerkman, D., McCulloch, C., Soininen, H., et al. (2006) · Brain · doi:10.1093/brain/awl269 · Cited by 586
Maintenance of peripheral naive T cells is sustained by thymus output in mice but not humans
den Braber, I., Mugwagwa, T., Vrisekoop, N., Westera, L., Mögling, R., Bregje de Boer, A., Willems, N., Schrijver, E. H. R., Spierenburg, G., Gaiser, K., et al. (2012) · Immunity · doi:10.1016/j.immuni.2012.02.006 · Cited by 572
Cancer Incidence After Retinoblastoma
Wong, F. L. (1997) · JAMA · doi:10.1001/jama.278.15.1262 · Cited by 694
A global nucleon optical model potential
Varner, R. L., Thompson, W. J., McAbee, T. L., Ludwig, E. J., & Clegg, T. B. (1991) · Physics Reports · doi:10.1016/0370-1573(91)90039-o · Cited by 564
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Carlberg, R. G., Yee, H. K. C., & Ellingson, E. (1997) · The Astrophysical Journal · doi:10.1086/303805 · Cited by 563
Dunn, O. J., Downie, N. M., & Heath, R. W. (1959) · Journal of the American Statistical Association · doi:10.2307/2282519 · Cited by 557
Haukoos, J. S., & Lewis, R. J. (2005) · Academic Emergency Medicine · doi:10.1197/j.aem.2004.11.018 · Cited by 546
Machine learning for perovskite materials design and discovery
Tao, Q., Xu, P., Li, M., & Lu, W. (2021) · npj Computational Materials · doi:10.1038/s41524-021-00495-8 · Cited by 542
Amato, F., Pandolfi, M., Escrig, A., Querol, X., Alastuey, A., Pey, J., Perez, N., & Hopke, P. K. (2009) · Atmospheric Environment · doi:10.1016/j.atmosenv.2009.02.039 · Cited by 584
Differential Galaxy Evolution in Cluster and Field Galaxies at z=0.3Preprint
Balogh, M. L., Morris, S. L., Yee, H. K. C., Carlberg, R. G., & Ellingson, E. (1999) · arXiv (Cornell University) · doi:10.48550/arxiv.astro-ph/9906470 · Cited by 520
Experimental Evidence That Competition Promotes Divergence in Adaptive Radiation
Schluter, D. (1994) · Science · doi:10.1126/science.266.5186.798 · Cited by 516
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Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012) · Journal of the Association for Information Systems · Cited by 520
Dueker, K. G., & Sheehan, A. F. (1997) · Journal of Geophysical Research Atmospheres · doi:10.1029/96jb03857 · Cited by 515
Reproductive Management of Lactating Dairy Cows Using Synchronization of Ovulation
Pursley, J. R., Kosorok, M. R., & Wiltbank, M. C. (1997) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(97)75938-1 · Cited by 511
Age-related Changes in Brain Activity across the Adult Lifespan
Grady, C. L., Springer, M. V., Hongwanishkul, D., McIntosh, A. R., & Winocur, G. (2006) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2006.18.2.227 · Cited by 497
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Grady, C. L., McIntosh, A. R., Beig, S., Keightley, M., Burian, H., & Black, S. E. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-03-00986.2003 · Cited by 504
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Twardowski, M. S., Boss, E., Sullivan, J. M., & Donaghay, P. L. (2004) · Marine Chemistry · doi:10.1016/j.marchem.2004.02.008 · Cited by 503
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Liu, J. H., Zingmond, D. S., McGory, M. L., SooHoo, N. F., Ettner, S. L., Brook, R. H., & Ko, C. Y. (2006) · JAMA · doi:10.1001/jama.296.16.1973 · Cited by 502
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Hjelmborg, J., Iachine, I. A., Skytthe, A., Vaupel, J. W., McGue, M. K., Koskenvuo, M. J., Kaprio, J. A., Pedersen, N. L., & Christensen, K. (2006) · Human Genetics · doi:10.1007/s00439-006-0144-y · Cited by 498
Ramratnam, B., Bonhoeffer, S., Binley, J. Μ., Hurley, A., Zhang, L., Mittler, J. E., Markowitz, M. H., Moore, J. P., Perelson, A. S., & Ho, D. D. (1999) · The Lancet · doi:10.1016/s0140-6736(99)02035-8 · Cited by 481
Suicidal behaviour: an epidemiological and genetic study
STATHAM, D. J., HEATH, A. C., MADDEN, P. A. F., BUCHOLZ, K. K., BIERUT, L., DINWIDDIE, S. H., SLUTSKE, W. S., DUNNE, M. P., & MARTIN, N. G. (1998) · Psychological Medicine · doi:10.1017/s0033291798006916 · Cited by 471
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Efron, B. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476768 · Cited by 471
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Bühlmann, P., & Bühlmann, P. (1997) · Bernoulli · doi:10.2307/3318584 · Cited by 461
A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns
Domazet‐Lošo, T., & Tautz, D. (2010) · Nature · doi:10.1038/nature09632 · Cited by 445
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Samuels, J. F., Bienvenu, O. J., Grados, M. A., Cullen, B., Riddle, M. A., Liang, K.-Y., Eaton, W. W., & Nestadt, G. (2008) · Behaviour Research and Therapy · doi:10.1016/j.brat.2008.04.004 · Cited by 452
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Manfred Mudelsee, A. (2018) · Earth-Science Reviews · doi:10.1016/j.earscirev.2018.12.005 · Cited by 453
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Abdi, H., & Williams, L. J. (2013) · Methods in Molecular Biology · doi:10.1007/978-1-62703-059-5_23 · Cited by 448
Metadata
- Authors
- Efron, B., & Tibshirani, R.
- ORCID
- Tibshirani, R.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 1986-02-01
- Volume
- 1
- Issue
- 1
- Pages
- 54-75
- ISSN
- 0883-4237 (ISSN-L)
- 2168-8745
- OpenAlex
- W2112688502
- Cited by
- 6,033
- References
- 34
- Citations by year
- 2026: 83 · 2025: 148 · 2024: 208 · 2023: 220 · 2022: 254 · 2021: 330 · 2020: 306 · 2019: 331 · 2018: 289 · 2017: 244 · 2016: 253 · 2015: 234 · 2014: 245 · 2013: 232 · 2012: 228
- FWCI
- 41.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Statistical Science (publishedVersion)
- Project Euclid (Cornell University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- bootstrapping, standard error estimation, confidence intervals, bias estimation, prediction error, time series, censored data, regression models, statistical accuracy
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 ›
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