The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
High-intensity exercise training increases the diversity and metabolic capacity of the mouse distal gut microbiota during diet-induced obesity
Open accessAbstract
Diet and exercise underpin the risk of obesity-related metabolic disease. Diet alters the gut microbiota, which contributes to aspects of metabolic disease during obesity. Repeated exercise provides metabolic benefits during obesity. We assessed whether exercise could oppose changes in the taxonomic and predicted metagenomic characteristics of the gut microbiota during diet-induced obesity. We hypothesized that high-intensity interval training (HIIT) would counteract high-fat diet (HFD)-induced changes in the microbiota without altering obesity in mice. Compared with chow-fed mice, an obesity-causing HFD decreased the Bacteroidetes-to-Firmicutes ratio and decreased the genetic capacity in the fecal microbiota for metabolic pathways such as the tricarboxylic acid (TCA) cycle. After HFD-induced obesity was established, a subset of mice were HIIT for 6 wk, which increased host aerobic capacity but did not alter body or adipose tissue mass. The effects of exercise training on the microbiota were gut segment dependent and more extensive in the distal gut. HIIT increased the alpha diversity and Bacteroidetes/Firmicutes ratio of the distal gut and fecal microbiota during diet-induced obesity. Exercise training increased the predicted genetic capacity related to the TCA cycle among other aspects of metabolism. Strikingly, the same microbial metabolism indexes that were increased by exercise were all decreased in HFD-fed vs. chow diet-fed mice. Therefore, exercise training directly opposed some of the obesity-related changes in gut microbiota, including lower metagenomic indexes of metabolism. Some host and microbial pathways appeared similarly affected by exercise. These exercise- and diet-induced microbiota interactions can be captured in feces.
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
“In accordance, animal studies by us and others have reported that high-intensity endurance training modified the gut microbiota (Campbell et al., 2016; Denou et al., 2016)”
From Six-Week Endurance Exercise Alters Gut Metagenome That Is not Reflected in Systemic Metabolism in Over-weight Women (2018) · cites this paper as Denou et al., 2016
In the citing paper
“In animal models exercise has boosted the abundance of Dorea (Allen et al., 2015; Denou et al., 2016)”
From Six-Week Endurance Exercise Alters Gut Metagenome That Is not Reflected in Systemic Metabolism in Over-weight Women (2018) · cites this paper as Denou et al., 2016
In the citing paper
“regular physical activity may help to combat reductions in butyrate-producing microbiota (Clostridiales, Roseburia, Lachnospiraceae, and Erysipelotrichaceae) [102] and Lactobacillus levels [103] that are commonly seen with aging [15, 84, 98].”
From Gut Microbiota Contribute to Age-Related Changes in Skeletal Muscle Size, Composition, and Function: Biological Basis for a Gut-Muscle Axis (2018) · cites this paper as [103]
In the citing paper
“correlations between microbial diversity and cardiorespiratory fitness [102] in concert with the exercise training mediated rescue of high-fat diet-induced microbial disturbance [103] support the idea that exercise training may impart beneficial effects on gut health.”
From Gut Microbiota Contribute to Age-Related Changes in Skeletal Muscle Size, Composition, and Function: Biological Basis for a Gut-Muscle Axis (2018) · cites this paper as [103]
Citations
Cites
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823
Obesity alters gut microbial ecology
Ley, R. E., Bäckhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504978102 · Cited by 6,176
Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., & Burcelin, R. (2008) · Diabetes · doi:10.2337/db07-1403 · Cited by 4,819
Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity
Everard, A., Belzer, C., Geurts, L., Ouwerkerk, J. P., Druart, C., Bindels, L. B., Guiot, Y., Derrien, M., Muccioli, G. G., Delzenne, N. M., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219451110 · Cited by 4,511
Gut Microbiota from Twins Discordant for Obesity Modulate Metabolism in Mice
Ridaura, V. K., Faith, J. J., Rey, F. E., Cheng, J., Duncan, A. E., Kau, A. L., Griffin, N. W., Lombard, V., Henrissat, B., Bain, J. R., et al. (2013) · Science · doi:10.1126/science.1241214 · Cited by 3,788
Turnbaugh, P. J., Bäckhed, F., Fulton, L., & Gordon, J. I. (2008) · Cell Host & Microbe · doi:10.1016/j.chom.2008.02.015 · Cited by 2,915
PANDAseq: paired-end assembler for Illumina sequences
Masella, A. P., Bartram, A. K., Truszkowski, J. M., Brown, D. G., & Neufeld, J. D. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-31 · Cited by 2,132
Adaptations of skeletal muscle to endurance exercise and their metabolic consequences
Holloszy, J. O., & Coyle, E. F. (1984) · Journal of Applied Physiology · doi:10.1152/jappl.1984.56.4.831 · Cited by 1,985
Cox, L. M., Yamanishi, S., Sohn, J., Alekseyenko, A. V., Leung, J. M., Cho, I., Kim, S. G., Li, H., Gao, Z., Mahana, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.05.052 · Cited by 1,859
Control of pathogens and pathobionts by the gut microbiota
Kamada, N., Chen, G. Y., Inohara, N., & Núñez, G. (2013) · Nature Immunology · doi:10.1038/ni.2608 · Cited by 1,625
Antibiotics in early life alter the murine colonic microbiome and adiposity
Cho, I., Yamanishi, S., Cox, L., Methé, B. A., Zavadil, J., Li, K., Gao, Z., Mahana, D., Raju, K., Teitler, I., et al. (2012) · Nature · doi:10.1038/nature11400 · Cited by 1,613
Exercise and associated dietary extremes impact on gut microbial diversity
Clarke, S. F., Murphy, E. F., O'Sullivan, O., Lucey, A. J., Humphreys, M., Hogan, A., Hayes, P., O'Reilly, M., Jeffery, I. B., Wood-Martin, R., et al. (2014) · Gut · doi:10.1136/gutjnl-2013-306541 · Cited by 1,439
Diet dominates host genotype in shaping the murine gut microbiota
Carmody, R. N., Gerber, G. K., Luevano, J. M., Gatti, D. M., Somes, L., Svenson, K. L., & Turnbaugh, P. J. (2015) · Cell Host & Microbe · doi:10.1016/j.chom.2014.11.010 · Cited by 1,103
Targeting gut microbiota in obesity: effects of prebiotics and probiotics
Delzenne, N. M., Neyrinck, A. M., Bäckhed, F., & Cani, P. D. (2011) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2011.126 · Cited by 805
Little, J. P., Gillen, J. B., Percival, M. E., Safdar, A., Tarnopolsky, M. A., Punthakee, Z., Jung, M. E., & Gibala, M. J. (2011) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00921.2011 · Cited by 787
Diet-Induced Dysbiosis of the Intestinal Microbiota and the Effects on Immunity and Disease
Brown, K., DeCoffe, D., Molcan, E., & Gibson, D. L. (2012) · Nutrients · doi:10.3390/nu4081095 · Cited by 700
Evans, C. C., LePard, K. J., Kwak, J. W., Stancukas, M. C., Laskowski, S., Dougherty, J., Moulton, L., Glawe, A., Wang, Y., Leone, V., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0092193 · Cited by 587
Sekirov, I., Tam, N. M., Jogova, M., Robertson, M. L., Li, Y., Lupp, C., & Finlay, B. B. (2008) · Infection and Immunity · doi:10.1128/iai.00319-08 · Cited by 500
Queipo-Ortuño, M. I., Seoane, L. M., Murri, M., Pardo, M., Gomez-Zumaquero, J. M., Cardona, F., Casanueva, F., & Tinahones, F. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065465 · Cited by 497
Gut microbiota, enteroendocrine functions and metabolism
Cani, P. D., Everard, A., & Duparc, T. (2013) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2013.09.008 · Cited by 378
MATSUMOTO, M., INOUE, R., TSUKAHARA, T., USHIDA, K., CHIJI, H., MATSUBARA, N., & HARA, H. (2008) · Bioscience, Biotechnology, and Biochemistry · doi:10.1271/bbb.70474 · Cited by 352
GuiTope: an application for mapping random-sequence peptides to protein sequences
Halperin, R. F., Stafford, P., Emery, J. S., Navalkar, K. A., & Johnston, S. A. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-1 · Cited by 348
Kang, S. S., Jeraldo, P., Kurti, A., Miller, M. E. B., Cook, M. D., Whitlock, K. G., Goldenfeld, N. D., Woods, J. A., White, B. A., Chia, N., et al. (2014) · Molecular Neurodegeneration · doi:10.1186/1750-1326-9-36 · Cited by 331
Mitochondrial citric acid cycle and related enzymes: Adaptive response to exercise
Holloszy, J. O., Oscai, L. B., Don, I., & Mole, P. A. (1970) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(70)90017-3 · Cited by 314
Dietary modulation of the microbiome affects autoinflammatory disease
Lukens, J. R., Gurung, P., Vogel, P., Johnson, G. R., Carter, R. A., McGoldrick, D. J., Bandi, S. R., Calabrese, C. R., Walle, L. V., Lamkanfi, M., et al. (2014) · Nature · doi:10.1038/nature13788 · Cited by 314
Voluntary and forced exercise differentially alters the gut microbiome in C57BL/6J mice
Allen, J. M., Berg Miller, M. E., Pence, B. D., Whitlock, K., Nehra, V., Gaskins, H. R., White, B. A., Fryer, J. D., & Woods, J. A. (2015) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01077.2014 · Cited by 266
NOD1 activators link innate immunity to insulin resistance
Schertzer, J. D., Tamrakar, A. K., Magalhães, J. G., Pereira, S., Bilan, P. J., Fullerton, M. D., Liu, Z., Steinberg, G. R., Giacca, A., Philpott, D. J., et al. (2011) · Diabetes · doi:10.2337/db11-0004 · Cited by 253
Self-citationGillen, J. B., Percival, M. E., Ludzki, A., Tarnopolsky, M. A., & Gibala, M. J. (2013) · Obesity · doi:10.1002/oby.20379 · Cited by 222
Ghosh, S., DeCoffe, D., Brown, K., Rajendiran, E., Estaki, M., Dai, C., Yip, A., & Gibson, D. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055468 · Cited by 214
Exercise training modifies gut microbiota in normal and diabetic mice
Lambert, J. E., Myslicki, J. P., Bomhof, M. R., Belke, D. D., Shearer, J., & Reimer, R. A. (2015) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2014-0452 · Cited by 214
Mika, A., Van Treuren, W., González, A., Herrera, J. J., Knight, R., & Fleshner, M. (2015) · PLOS ONE · doi:10.1371/journal.pone.0125889 · Cited by 197
Denou, E., Lolmède, K., Garidou, L., Pomié, C., Chabo, C., Lau, T. C., Fullerton, M. D., Nigro, G., Zakaroff‐Girard, A., Luche, É., et al. (2015) · EMBO Molecular Medicine · doi:10.15252/emmm.201404169 · Cited by 197
Self-citationSegal, K. R., Edaño, A., Abalos, A. M., Albu, J., Blando, L., Tomas, M. B., & Pi‐Sunyer, F. X. (1991) · Journal of Applied Physiology · doi:10.1152/jappl.1991.71.6.2402 · Cited by 186
Brown, K., Godovannyi, A., Ma, C., Zhang, Y., Zahra, A.-V., Dai, C., Gorzelak, M. A., Chan, Y.-K., Chan, J. M., Lochner, A., et al. (2015) · The ISME Journal · doi:10.1038/ismej.2015.114 · Cited by 179
O’Sullivan, Ó., Cronin, O., Clarke, S. F., Murphy, E. F., Molloy, M., Shanahan, F., & Cotter, P. D. (2015) · Gut Microbes · doi:10.1080/19490976.2015.1011875 · Cited by 174
Steinberg, G. R., O'Neill, H. M., Dzamko, N. L., Galic, S., Naim, T., Koopman, R., Jørgensen, S. B., Honeyman, J., Hewitt, K., Chen, Z.-P., et al. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.102434 · Cited by 164
Self-citationCook, M. D., Martin, S. A., Williams, C., Whitlock, K., Wallig, M. A., Pence, B. D., & Woods, J. A. (2013) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2013.05.005 · Cited by 153
Deletion of Skeletal Muscle SOCS3 Prevents Insulin Resistance in Obesity
Jørgensen, S. B., O’Neill, H. M., Sylow, L., Honeyman, J. E., Hewitt, K. A., Palanivel, R., Fullerton, M. D., Öberg, L., Balendran, A., Galić, S., et al. (2012) · Diabetes · doi:10.2337/db12-0443 · Cited by 152
Self-citationSteinberg, G. R., & Schertzer, J. D. (2014) · Immunology and Cell Biology · doi:10.1038/icb.2014.11 · Cited by 150
Self-citationAMPK‐independent pathways regulate skeletal muscle fatty acid oxidation
Dzamko, N., Schertzer, J. D., Ryall, J. G., Steel, R., Macaulay, S. L., Wee, S., Chen, Z., Michell, B. J., Oakhill, J. S., Watt, M. J., et al. (2008) · The Journal of Physiology · doi:10.1113/jphysiol.2008.159814 · Cited by 147
Self-citationHigh intensity interval training improves liver and adipose tissue insulin sensitivity
Marcinko, K., Sikkema, S. R., Samaan, M. C., Kemp, B. E., Fullerton, M. D., & Steinberg, G. R. (2015) · Molecular Metabolism · doi:10.1016/j.molmet.2015.09.006 · Cited by 146
Self-citationClinical Consequences of Diet-Induced Dysbiosis
Chan, Y. K., Estaki, M., & Gibson, D. L. (2013) · Annals of Nutrition and Metabolism · doi:10.1159/000354902 · Cited by 140
Altered regional blood flow responses to submaximal exercise in older rats
Musch, T. I., Eklund, K. E., Hageman, K. S., & Poole, D. C. (2004) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00729.2003 · Cited by 140
Cook, M. D., Allen, J. M., Pence, B. D., Wallig, M. A., Gaskins, H. R., White, B. A., & Woods, J. A. (2016) · Immunology & Cell Biology · doi:10.1038/icb.2015.108 · Cited by 140
Ye, Y. (2010) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2010.5706555 · Cited by 117
NOD2 Activation Induces Muscle Cell-Autonomous Innate Immune Responses and Insulin Resistance
Tamrakar, A. K., Schertzer, J. D., Chiu, T. T., Foley, K. P., Bilan, P. J., Philpott, D. J., & Klip, A. (2010) · Endocrinology · doi:10.1210/en.2010-0437 · Cited by 107
Self-citationDiets rich in n -6 PUFA induce intestinal microbial dysbiosis in aged mice
Ghosh, S., Molcan, E., DeCoffe, D., Dai, C., & Gibson, D. L. (2013) · British Journal Of Nutrition · doi:10.1017/s0007114512005326 · Cited by 100
Training effects on regional blood flow response to maximal exercise in foxhounds
Musch, T. I., Haidet, G. C., Ordway, G. A., Longhurst, J. C., & Mitchell, J. H. (1987) · Journal of Applied Physiology · doi:10.1152/jappl.1987.62.4.1724 · Cited by 95
McPhee, J. B., & Schertzer, J. D. (2015) · Clinical Science · doi:10.1042/cs20150431 · Cited by 86
Self-citationIs the GI System Built For Exercise?
GISOLFI, C. V. (2000) · Physiology · doi:10.1152/physiologyonline.2000.15.3.114 · Cited by 84
Bacterial Peptidoglycan Stimulates Adipocyte Lipolysis via NOD1
Chi, W., Dao, D., Lau, T. C., Henriksbo, B. D., Cavallari, J. F., Foley, K. P., & Schertzer, J. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097675 · Cited by 78
Self-citationImmunometabolism of AMPK in insulin resistance and atherosclerosis
Fullerton, M. D., Steinberg, G. R., & Schertzer, J. D. (2012) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2012.02.004 · Cited by 73
Self-citationCavallari, J. F., Denou, E., Foley, K. P., Khan, W. I., & Schertzer, J. D. (2016) · Gut Microbes · doi:10.1080/19490976.2015.1127481 · Cited by 55
Self-citationSchein, C. H., Bowen, D. M., Lewis, J. A., Choi, K., Paul, A. V., van Noort, G. J. V. D. H., Lu, W., & Filippov, D. V. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-s13-s9 · Cited by 28
Regulation of Muscle Genes by Moderate Exercise
Nishida, Y., Tanaka, H., Tobina, T., Murakami, K., Shono, N., Shindo, M., Ogawa, W., Yoshioka, M., & St‐Amand, J. (2010) · International Journal of Sports Medicine · doi:10.1055/s-0030-1255065 · Cited by 26
Rapid orocecal transit in chronically active persons with high energy intake
Harris, A., Lindeman, A. K., & Martin, B. (1991) · Journal of Applied Physiology · doi:10.1152/jappl.1991.70.4.1550 · Cited by 24
Research works printed but not linked: 2
- O'Sullivan O, 2015, Gut Microbes, 1
- Ye Y, 2011, Proc IEEE Internl Conf Bioinformatics Biomed, 2010, 153
Cited by
Sorted by citations
Dysbiosis and the immune system
Levy, M., Kolodziejczyk, A. A., Thaiss, C. A., & Elinav, E. (2017) · Nature Reviews Immunology · doi:10.1038/nri.2017.7 · Cited by 1,769
Liu, B., Liu, X., Liang, Z., & Wang, J. (2021) · World Journal of Gastroenterology · doi:10.3748/wjg.v27.i25.3837 · Cited by 662
Effects of Psychological, Environmental and Physical Stressors on the Gut Microbiota
Karl, J. P., Hatch‐McChesney, A., Arcidiacono, S. M., Pearce, S., Pantoja-Feliciano, I. G., Doherty, L. A., & Soares, J. W. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.02013 · Cited by 563
Mailing, L. J., Allen, J. M., Buford, T. W., Fields, C. J., & Woods, J. A. (2019) · Exercise and Sport Sciences Reviews · doi:10.1249/jes.0000000000000183 · Cited by 521
Differences in gut microbiota profile between women with active lifestyle and sedentary women
Bressa, C., Bailén-Andrino, M., Pérez-Santiago, J., González-Soltero, R., Pérez, M., Montalvo-Lominchar, M. G., Maté-Muñoz, J. L., Domínguez, R., Moreno, D., & Larrosa, M. (2017) · PLOS ONE · doi:10.1371/journal.pone.0171352 · Cited by 501
Metadata
- Authors
- Denou, E., Marcinko, K., Surette, M. G., Steinberg, G. R., & Schertzer, J. D.
- Affiliations
- McMaster University (CA)
- Corresponding author
- Schertzer, Jonathan D.
- Venue
- American Journal of Physiology-Endocrinology and Metabolism
- Publisher
- American Physiological Society
- Published
- 2016-06-01
- Volume
- 310
- Issue
- 11
- Pages
- E982-E993
- ISSN
- 0193-1849 (ISSN-L)
- 1522-1555
- PMC
- PMC4935139
- OpenAlex
- W2342902276
- Cited by
- 260
- References
- 61
- Citations by year
- 2026: 24 · 2025: 17 · 2024: 21 · 2023: 35 · 2022: 36 · 2021: 28 · 2020: 27 · 2019: 28 · 2018: 20 · 2017: 21 · 2016: 3
- FWCI
- 12.47
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- American Journal of Physiology-Endocrinology and Metabolism (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research (136665_1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- high-intensity interval training, diet-induced obesity, gut microbiota, high-fat diet, Firmicutes/Bacteroidetes ratio, TCA cycle, alpha diversity, cardiorespiratory fitness, obesity-related metabolic diseases, host-microbe interactions
- MeSH terms
- Gastrointestinal Microbiome, High-Intensity Interval Training, Animals, Bacteria, Exercise Therapy, Male, Mice, Inbred C57BL, Obesity, Physical Conditioning, Animal, Treatment Outcome, Biodiversity, Mice, Metagenome, Diet, High-Fat
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
