The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Blood-Borne Markers of Fatigue in Competitive Athletes – Results from Simulated Training Camps
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.
Integrity signals
Registry
Cites
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.
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
“The assessment of blood-borne markers can be useful for determining an optimal training strategy on an individual basis and athletic performance levels [23,24].”
From The Associations of Vitamin D Status with Athletic Performance and Blood-borne Markers in Adolescent Athletes: A Cross-Sectional Study (2019) · cites this paper as [24]
In the citing paper
“It also provides precise and reliable measurements of the physiological response to identify the stress-to-recovery status.”
From The Associations of Vitamin D Status with Athletic Performance and Blood-borne Markers in Adolescent Athletes: A Cross-Sectional Study (2019) · cites this paper as [24]
In the citing paper
“The status of training intensity or overtraining syndromes can be determined by examining blood-borne markers such as plasma free testosterone (FT), cortisol (C), creatine kinase (CK), and urea (U).”
From The Associations of Vitamin D Status with Athletic Performance and Blood-borne Markers in Adolescent Athletes: A Cross-Sectional Study (2019) · cites this paper as [24]
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
(2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318279a10a · Cited by 1,233
Halson, S. L., Bridge, M. W., Meeusen, R., Busschaert, B., Gleeson, M., Jones, D. A., & Jeukendrup, A. E. (2002) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01164.2001 · Cited by 304
Research works printed but not linked: 23
- CD Paton, 2001, Tests of cycling performance, Sports Med, 31, 489, 10.2165/00007256-200131070-00004 · DOI · Paper page
- DJ Smith, 2000, Changes in glutamine and glutamate concentrations for tracking training tolerance, Med Sci Sports Exerc, 32, 684, 10.1097/00005768-200003000-00020 · DOI
- JM Steinacker, 2004, New aspects of the hormone and cytokine response to training, Eur J Appl Physiol, 91, 382, 10.1007/s00421-003-0960-x · DOI
- A Urhausen, 1995, Blood hormones as markers of training stress and overtraining, Sports Med, 20, 251, 10.2165/00007256-199520040-00004 · DOI · Paper page
- HH Gabriel, 1998, Overtraining and immune system: a prospective longitudinal study in endurance athletes, Med Sci Sports Exerc, 30, 1151, 10.1097/00005768-199807000-00021 · DOI
- T Meyer, 2004, Different effects of two regeneration regimens on immunological parameters in cyclists, Med Sci Sports Exerc, 36, 1743, 10.1249/01.MSS.0000142422.87805.74 · DOI
- M Kellmann, 2010, Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring, Scand J Med Sci Sports, 20, 95, 10.1111/j.1600-0838.2010.01192.x · DOI · Paper page
- P Kaikkonen, 2008, Post-exercise heart rate variability of endurance athletes after different high-intensity exercise interventions, Scand J Med Sci Sports, 18, 511, 10.1111/j.1600-0838.2007.00728.x · DOI
- M Buchheit, 2014, Monitoring training status with HR measures: do all roads lead to Rome?, Front Physiol, 5, 73, 10.3389/fphys.2014.00073 · DOI · Paper page
- A Urhausen, 2002, Diagnosis of overtraining: what tools do we have?, Sports Med, 32, 95, 10.2165/00007256-200232020-00002 · DOI · Paper page
- EW Faria, 2005, The science of cycling: physiology and training—part 1, Sports Med, 35, 285, 10.2165/00007256-200535040-00002 · DOI · Paper page
- A Urhausen, 1998, Impaired pituitary hormonal response to exhaustive exercise in overtrained endurance athletes, Med Sci Sports Exerc, 30, 407, 10.1097/00005768-199803000-00011 · DOI
- M Parry-Billings, 1992, Plasma amino acid concentrations in the overtraining syndrome: possible effects on the immune system, Med Sci Sports Exerc, 24, 1353, 10.1249/00005768-199212000-00008 · DOI
- F Areces, 2015, Changes in Serum Free Amino Acids and Muscle Fatigue Experienced during a Half-Ironman Triathlon, PLoS One, 10, e0138376, 10.1371/journal.pone.0138376 · DOI
- PE Sottas, 2007, Bayesian detection of abnormal values in longitudinal biomarkers with an application to T/E ratio, Biostatistics, 8, 285, 10.1093/biostatistics/kxl009 · DOI
- PE Sottas, 2012, Current implementation and future of the Athlete Biological Passport, Bioanalysis, 4, 1645, 10.4155/bio.12.130 · DOI
- A Jeukendrup, 1996, A new validated endurance performance test, Med Sci Sports Exerc, 28, 266, 10.1097/00005768-199602000-00017 · DOI · Paper page
- RP Lamberts, 2010, Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist, Eur J Appl Physiol, 108, 183, 10.1007/s00421-009-1291-3 · DOI
- PB Laursen, 2003, Reproducibility of a laboratory-based 40-km cycle time-trial on a stationary wind-trainer in highly trained cyclists, Int J Sports Med, 24, 481, 10.1055/s-2003-42012 · DOI
- GS Palmer, 1996, Assessment of the reproducibility of performance testing on an air-braked cycle ergometer, Int J Sports Med, 17, 293, 10.1055/s-2007-972849 · DOI
- A Hecksteden, 2015, Individual response to exercise training—a statistical perspective, J Appl Physiol (1985)
- A Sassi, 2008, Seasonal changes in aerobic fitness indices in elite cyclists, Appl Physiol Nutr Metab, 33, 735, 10.1139/H08-046 · DOI
- B Fernandez-Garcia, 2002, The response of sexual and stress hormones of male pro-cyclists during continuous intense competition, Int J Sports Med, 23, 555, 10.1055/s-2002-35532 · DOI
Cited by
Achievements and Challenges for Real-Time Sensing of Analytes in Sweat within Wearable Platforms
Brothers, M. C., DeBrosse, M., Grigsby, C. C., Naik, R. R., Hussain, S. M., Heikenfeld, J., & Kim, S. S. (2019) · Accounts of Chemical Research · doi:10.1021/acs.accounts.8b00555 · Cited by 207
Gastin, P. B., Hunkin, S. L., Fahrner, B., & Robertson, S. (2019) · Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000003023 · Cited by 82
Seo, M.-W., Song, J. K., Jung, H. C., Kim, S.-W., Kim, J.-H., & Lee, J.-M. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16183422 · Cited by 34
Metadata
- Authors
- Hecksteden, A., Skorski, S., Schwindling, S., Hammes, D., Pfeiffer, M., Kellmann, M., Ferrauti, A., & Meyer, T.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-02-18
- Volume
- 11
- Issue
- 2
- Pages
- e0148810
- ISSN
- 1932-6203
- Cited by
- 64
- References
- 2
- Language
- en
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.