The DOI matches its Crossref record; 81 of the 81 references it cites were found in a registry or an index.
Systems Toxicology: From Basic Research to Risk Assessment
Open accessAbstract
Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.
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.
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
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
KEGG for integration and interpretation of large-scale molecular data sets
Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., & Tanabe, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr988 · Cited by 4,848
Minimum information about a microarray experiment (MIAME)-toward standards for microarray data
Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., et al. (2001) · Nature Genetics · doi:10.1038/ng1201-365 · Cited by 4,109
Goecks, J., Nekrutenko, A., Taylor, J., & The Galaxy Team (2010) · Genome Biology · doi:10.1186/gb-2010-11-8-r86 · Cited by 3,453
Ankley, G. T., Bennett, R. S., Erickson, R. J., Hoff, D. J., Hornung, M. W., Johnson, R. D., Mount, D. R., Nichols, J. W., Russom, C. L., Schmieder, P. K., et al. (2009) · Environmental Toxicology and Chemistry · doi:10.1002/etc.34 · Cited by 2,734
Wild, C. P. (2005) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-05-0456 · Cited by 2,562
Activities at the Universal Protein Resource (UniProt)
(2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1140 · Cited by 1,735
The exposome: from concept to utility
Wild, C. P. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr236 · Cited by 1,416
The ToxCast Program for Prioritizing Toxicity Testing of Environmental Chemicals
Dix, D. J., Houck, K. A., Martin, M. T., Richard, A. M., Setzer, R. W., & Kavlock, R. J. (2007) · Toxicological Sciences · doi:10.1093/toxsci/kfl103 · Cited by 1,012
Self-citationTaverna: a tool for building and running workflows of services
Hull, D., Wolstencroft, K., Stevens, R., Goble, C., Pocock, M. R., Li, P., & Oinn, T. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl320 · Cited by 943
Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks
Fiehn, O. (2001) · Comparative and Functional Genomics · doi:10.1002/cfg.82 · Cited by 934
Dunn, W. B., Broadhurst, D. I., Atherton, H. J., Goodacre, R., & Griffin, J. L. (2011) · Chem. Soc. Rev. · doi:10.1039/b906712b · Cited by 860
Rappaport, S. M., & Smith, M. T. (2010) · Science · doi:10.1126/science.1192603 · Cited by 846
Global burden of disease and risk factors
(2007) · Choice Reviews Online · doi:10.5860/choice.44-4479 · Cited by 825
The minimum information about a proteomics experiment (MIAPE)
Taylor, C. F., Paton, N. W., Lilley, K. S., Binz, P.-A., Julian, R. K., Jones, A. R., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E. W., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1329 · Cited by 766
The BioPAX community standard for pathway data sharing
Demir, E., Cary, M. P., Paley, S., Fukuda, K., Lemer, C., Vastrik, I., Wu, G., D'Eustachio, P., Schaefer, C., Luciano, J., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1666 · Cited by 745
WikiPathways: Pathway Editing for the People
Pico, A. R., Kelder, T., van Iersel, M. P., Hanspers, K., Conklin, B. R., & Evelo, C. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060184 · Cited by 701
Update on activities at the Universal Protein Resource (UniProt) in 2013
The UniProt Consortium (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1068 · Cited by 672
Lipidomics: New Tools and Applications
Wenk, M. R. (2010) · Cell · doi:10.1016/j.cell.2010.11.033 · Cited by 589
Gene Ontology Annotations and Resources
The Gene Ontology Consortium (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1050 · Cited by 553
Metabonomics in Toxicology: A Review
Robertson, D. G. (2005) · Toxicological Sciences · doi:10.1093/toxsci/kfi102 · Cited by 541
WikiPathways: building research communities on biological pathways
Kelder, T., van Iersel, M. P., Hanspers, K., Kutmon, M., Conklin, B. R., Evelo, C. T., & Pico, A. R. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1074 · Cited by 522
Kavlock, R., Chandler, K., Houck, K., Hunter, S., Judson, R., Kleinstreuer, N., Knudsen, T., Martin, M., Padilla, S., Reif, D., et al. (2012) · Chemical Research in Toxicology · doi:10.1021/tx3000939 · Cited by 494
Self-citationToxicogenomics and systems toxicology: aims and prospects
Waters, M. D., & Fostel, J. M. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1493 · Cited by 415
Wetmore, B. A., Wambaugh, J. F., Ferguson, S. S., Sochaski, M. A., Rotroff, D. M., Freeman, K., Clewell, H. J., Dix, D. J., Andersen, M. E., Houck, K. A., et al. (2012) · Toxicological Sciences · doi:10.1093/toxsci/kfr254 · Cited by 415
Self-citationEnvironmental Epigenetics and Its Implication on Disease Risk and Health Outcomes
Ho, S.-M., Johnson, A., Tarapore, P., Janakiram, V., Zhang, X., & Leung, Y.-K. (2012) · ILAR Journal · doi:10.1093/ilar.53.3-4.289 · Cited by 312
Peer Reviewed: Internal Exposure: Linking Bioavailability to Effects
Escher, B. I., & Hermens, J. L. M. (2004) · Environmental Science & Technology · doi:10.1021/es0406740 · Cited by 274
A roadmap for the development of alternative (non-animal) methods for systemic toxicity testing
Basketter, D. (2012) · ALTEX · doi:10.14573/altex.2012.1.003 · Cited by 225
High-Throughput Models for Exposure-Based Chemical Prioritization in the ExpoCast Project
Wambaugh, J. F., Setzer, R. W., Reif, D. M., Gangwal, S., Mitchell-Blackwood, J., Arnot, J. A., Joliet, O., Frame, A., Rabinowitz, J., Knudsen, T. B., et al. (2013) · Environmental Science & Technology · doi:10.1021/es400482g · Cited by 222
Metabolomics in toxicology and preclinical research
Ramirez, T. (2013) · ALTEX · doi:10.14573/altex.2013.2.209 · Cited by 220
A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB
Rayner, T. F., Rocca-Serra, P., Spellman, P. T., Causton, H. C., Farne, A., Holloway, E., Irizarry, R. A., Liu, J., Maier, D. S., Miller, M., et al. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-489 · Cited by 217
Evolution of Translational Omics: Lessons Learned and the Path Forward
Committee on the Review of Omics-Based Tests for Predicting Patient Outcomes in Clinical Trials, Board on Health Care Services, Board on Health Sciences Policy, & Institute of Medicine (2012) · National Academies Press eBooks · doi:10.17226/13297 · Cited by 200
Bouhifd, M., Hartung, T., Hogberg, H. T., Kleensang, A., & Zhao, L. (2013) · Journal of Applied Toxicology · doi:10.1002/jat.2874 · Cited by 187
caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid
Saltz, J., Oster, S., Hastings, S., Langella, S., Kurc, T., Sanchez, W., Kher, M., Manisundaram, A., Shanbhag, K., & Covitz, P. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl272 · Cited by 186
Computational Toxicology—A State of the Science Mini Review
Kavlock, R. J., Ankley, G., Blancato, J., Breen, M., Conolly, R., Dix, D., Houck, K., Hubal, E., Judson, R., Rabinowitz, J., et al. (2008) · Toxicological Sciences · doi:10.1093/toxsci/kfm297 · Cited by 181
Self-citationAdductomics: Characterizing exposures to reactive electrophiles
Rappaport, S. M., Li, H., Grigoryan, H., Funk, W. E., & Williams, E. R. (2012) · Toxicology Letters · doi:10.1016/j.toxlet.2011.04.002 · Cited by 180
High throughput quantitative molecular lipidomics
Jung, H. R., Sylvänne, T., Koistinen, K. M., Tarasov, K., Kauhanen, D., & Ekroos, K. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2011.06.025 · Cited by 168
Stevens, R. (2004) · Dictionary of Bioinformatics and Computational Biology · doi:10.1002/9780471650126.dob0273.pub2 · Cited by 153
Patel, C. J., Cullen, M. R., Ioannidis, J. P. A., & Butte, A. J. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys003 · Cited by 149
Environmental Toxicants, Epigenetics, and Cancer
Pogribny, I. P., & Rusyn, I. (2012) · Advances in experimental medicine and biology · doi:10.1007/978-1-4419-9967-2_11 · Cited by 137
Systems Pharmacology to Predict Drug Toxicity: Integration Across Levels of Biological Organization
Bai, J. P. F., & Abernethy, D. R. (2012) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-011112-140248 · Cited by 133
Transcriptomics in ecotoxicology
Schirmer, K., Fischer, B. B., Madureira, D. J., & Pillai, S. (2010) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-010-3662-3 · Cited by 127
Self-citationBiomarkers intersect with the exposome
Rappaport, S. M. (2012) · Biomarkers · doi:10.3109/1354750x.2012.691553 · Cited by 114
Metabolomics in nutrition research: current status and perspectives
Brennan, L. (2013) · Biochemical Society Transactions · doi:10.1042/bst20120350 · Cited by 107
Howell, B. A., Yang, Y., Kumar, R., Woodhead, J. L., Harrill, A. H., M.A., H. J. C. I., Andersen, M. E., Siler, S. Q., & Watkins, P. B. (2012) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-012-9266-0 · Cited by 106
Metabolomics-on-a-Chip and Predictive Systems Toxicology in Microfluidic Bioartificial Organs
Shintu, L., Baudoin, R., Navratil, V., Prot, J. M., Pontoizeau, C., Defernez, M., Blaise, B. J., Domange, C., Péry, A. R. R., Toulhoat, P., et al. (2012) · Analytical Chemistry · doi:10.1021/ac2011075 · Cited by 104
Martin, F. P., Thomson, T. M., Sewer, A., Drubin, D. A., Mathis, C., Weisensee, D., Pratt, D. R., Hoeng, J., & Peitsch, M. C. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-54 · Cited by 103
Self-citationMetabolomics in Plants and Humans: Applications in the Prevention and Diagnosis of Diseases
Gomez‐Casati, D. F., Zanor, M. I., & Busi, M. V. (2013) · BioMed Research International · doi:10.1155/2013/792527 · Cited by 101
Disruption of embryonic vascular development in predictive toxicology
Knudsen, T. B., & Kleinstreuer, N. (2011) · Birth Defects Research Part C Embryo Today Reviews · doi:10.1002/bdrc.20223 · Cited by 98
Catlett, N. L., Bargnesi, A. J., Ungerer, S., Seagaran, T., Ladd, W., Elliston, K. O., & Pratt, D. R. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-340 · Cited by 97
Härtung, T. (2012) · ALTEX · doi:10.14573/altex.2012.2.119 · Cited by 97
A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue
Schlage, W. K., Westra, J. W., Gebel, S., Catlett, N. L., Mathis, C., Frushour, B. P., Hengstermann, A., Hooser, A. A. V., Poussin, C., Wong, B., et al. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-168 · Cited by 77
Self-citationGenomic impact of cigarette smoke, with application to three smoking-related diseases
Talikka, M., Sierro, N., Ivanov, N. V., Chaudhary, N. I., Peck, M. J., Hoeng, J., Coggins, C. R. E., & Peitsch, M. C. (2012) · Critical Reviews in Toxicology · doi:10.3109/10408444.2012.725244 · Cited by 74
Self-citationSchmidt, B. J., Casey, F., Paterson, T. S., & Chan, J. R. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-221 · Cited by 72
Case study: the role of mechanistic network models in systems toxicology
Hoeng, J., Talikka, M., Martin, F. P., Sewer, A., Yang, X., Iskandar, A. R., Schlage, W. K., & Peitsch, M. C. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.07.023 · Cited by 71
Self-citationGenomics and transcriptomics in drug discovery
Dopazo, J. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.06.003 · Cited by 70
Discovering environmental causes of disease
Rappaport, S. M. (2011) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2011-200726 · Cited by 68
Modeling Drug- and Chemical-Induced Hepatotoxicity with Systems Biology Approaches
Bhattacharya, S., Shoda, L. K. M., Zhang, Q., Woods, C. G., Howell, B. A., Siler, S. Q., Woodhead, J. L., Yang, Y., McMullen, P. D., Watkins, P. B., et al. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00462 · Cited by 67
An environmental wide association study (EWAS) approach to the metabolic syndrome
Lind, P., Risérus, U., Salihović, S., van Bavel, B., & Lind, L. (2013) · Environment International · doi:10.1016/j.envint.2013.01.017 · Cited by 66
Construction of a computable cell proliferation network focused on non-diseased lung cells
Westra, J. W., Schlage, W. K., Frushour, B. P., Gebel, S., Catlett, N. L., Han, W., Eddy, S. F., Hengstermann, A., Matthews, A. L., Mathis, C., et al. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-105 · Cited by 63
Self-citationThomson, T. M., Sewer, A., Martin, F. P., Belcastro, V., Frushour, B. P., Gebel, S., Park, J., Schlage, W. K., Talikka, M., Vasilyev, D. M., et al. (2013) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2013.07.007 · Cited by 62
Self-citationIskandar, A. R., Martin, F. P., Talikka, M., Schlage, W. K., Kostadinova, R. M., Mathis, C., Hoeng, J., & Peitsch, M. C. (2013) · BioMed Research International · doi:10.1155/2013/512086 · Cited by 59
Self-citationConstruction of a Computable Network Model for DNA Damage, Autophagy, Cell Death, and Senescence
Gebel, S., Lichtner, R. B., Frushour, B. P., Schlage, W. K., Hoang, V., Talikka, M., Hengstermann, A., Mathis, C., Veljkovic, E., Peck, M. J., et al. (2013) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s11154 · Cited by 58
Self-citationShoda, L. K. M., Kreuwel, H. T. C., Gadkar, K. G., Zheng, Y., Whiting, C. C., Atkinson, M. A., Bluestone, J. A., Mathis, D. J., Young, D. L., & Ramanujan, S. (2010) · Clinical & Experimental Immunology · doi:10.1111/j.1365-2249.2010.04166.x · Cited by 56
Systems biology for battling rheumatoid arthritis: Application of the Entelos PhysioLab platform
Rullmann, J. A. C., Struemper, H., Defranoux, N. A., Ramanujan, S., Meeuwisse, C. M., & van Elsas, A. (2005) · Systems Biology · doi:10.1049/ip-syb:20050053 · Cited by 56
A Modular Cell-Type Focused Inflammatory Process Network Model for Non-Diseased Pulmonary Tissue
Westra, J. W., Schlage, W. K., Hengstermann, A., Gebel, S., Mathis, C., Thomson, T. M., Wong, B., Hoang, V., Veljkovic, E., Peck, M. J., et al. (2013) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s11509 · Cited by 53
Self-citationThe Role of Metabolomics in Characterizing The Human Exposome
Athersuch, T. J. (2012) · Bioanalysis · doi:10.4155/bio.12.211 · Cited by 49
Xing, H., MCDONAGH, P. D., Bienkowska, J. R., Cashorali, T., Runge, K., Miller, R. E., DeCaprio, D., Church, B., Roubenoff, R., Khalil, I. G., et al. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001105 · Cited by 40
Social engineering for virtual 'big science' in systems biology
Kitano, H., Ghosh, S., & Matsuoka, Y. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.574 · Cited by 40
Phosphoproteomics in drug discovery
Morris, M. K., Chi, A., Melas, I. N., & Alexopoulos, L. G. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.10.010 · Cited by 38
Application of a Systems Biology Approach to Skin Allergy Risk Assessment
Maxwell, G., & Mackay, C. D. A. (2008) · Alternatives to Laboratory Animals · doi:10.1177/026119290803600510 · Cited by 37
Cell Surface Capturing Technologies for the Surfaceome Discovery of Hepatocytes
Bausch‐Fluck, D., Hofmann, A., & Wollscheid, B. (2012) · Methods in molecular biology · doi:10.1007/978-1-61779-959-4_1 · Cited by 33
Biological network inference for drug discovery
Lecca, P., & Priami, C. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.11.001 · Cited by 32
The contribution of physicochemical properties to multiple in vitro cytotoxicity endpoints
Lu, S., Jessen, B. A., Strock, C., & Will, Y. (2012) · Toxicology in Vitro · doi:10.1016/j.tiv.2012.01.025 · Cited by 28
On Crowd-verification of Biological Networks
Ansari, S., Binder, J., Boué, S., Fabio, A. D., Hayes, W., Hoeng, J., Iskandar, A. R., Kleiman, R. J., Norel, R., O'neel, B., et al. (2013) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s12932 · Cited by 28
Self-citationMetabolomics: Integration of a New “Omics” with Clinical Pharmacology
James, L. P. (2013) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2013.166 · Cited by 28
Breen, M., Villeneuve, D. L., Ankley, G. T., Bencic, D. C., Breen, M. S., Watanabe, K. H., Lloyd, A. L., & Conolly, R. B. (2013) · Toxicological Sciences · doi:10.1093/toxsci/kft067 · Cited by 26
Vihervaara, T., Suoniemi, M., & Laaksonen, R. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.09.008 · Cited by 24
Practical Application of Toxicogenomics for Profiling Toxicant-Induced Biological Perturbations
Kiyosawa, N., Manabe, S., Yamoto, T., & Sanbuissho, A. (2010) · International Journal of Molecular Sciences · doi:10.3390/ijms11093397 · Cited by 22
Food for Thought … Systems Toxicology
Härtung, T., van Vliet, E., Jaworska, J. S., Bonilla, L. E., Skinner, N., & Thomas, R. S. (2012) · Cited by 20
Belcastro, V., Poussin, C., Gebel, S., Mathis, C., Schlage, W. K., Lichtner, R. B., Quadt‐Humme, S., Wagner, S., Hoeng, J., & Peitsch, M. C. (2013) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s12167 · Cited by 10
Self-citation
Cited by
In silico ADME/T modelling for rational drug design
Wang, Y., Xing, J., Xu, Y., Zhou, N., Peng, J., Xiong, Z., Liu, X., Luo, X., Luo, C., Chen, K., et al. (2015) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583515000190 · Cited by 367
Judson, R., Houck, K., Martin, M., Richard, A. M., Knudsen, T. B., Shah, I., Little, S., Wambaugh, J., Woodrow Setzer, R., Kothya, P., et al. (2016) · Toxicological Sciences · doi:10.1093/toxsci/kfw092 · Cited by 232
Human in vitro models of nonalcoholic fatty liver disease
Müller, F. A., & Sturla, S. J. (2019) · Current Opinion in Toxicology · doi:10.1016/j.cotox.2019.03.001 · Cited by 118
Self-citationFarrera, C., & Fadeel, B. (2015) · European Journal of Pharmaceutics and Biopharmaceutics · doi:10.1016/j.ejpb.2015.03.007 · Cited by 92
Murphy, J., Gaca, M., Lowe, F., Minet, E., Breheny, D., Prasad, K., Camacho, O., Fearon, I. M., Liu, C., Wright, C., et al. (2017) · Regulatory Toxicology and Pharmacology · doi:10.1016/j.yrtph.2017.09.008 · Cited by 71
Metadata
- Authors
- Sturla, S. J., Boobis, A. R., FitzGerald, R. E., Hoeng, J., Kavlock, R. J., Schirmer, K., Whelan, M., Wilks, M. F., & Peitsch, M. C.
- Venue
- Chemical Research in Toxicology
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-01-21
- Volume
- 27
- Issue
- 3
- Pages
- 314-329
- ISSN
- 0893-228X (ISSN-L)
- 1520-5010
- OpenAlex
- W1976750784
- Cited by
- 366
- References
- 81
- FWCI
- 15.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
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.