The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Understanding Information Technology Usage: A Test of Competing Models
Abstract
The Technology Acceptance Model and two variations of the Theory of Planned Behavior were compared to assess which model best helps to understand usage of information technology. The models were compared using student data collected from 786 potential users of a computer resource center. Behavior data was based on monitoring 3,780 visits to the resource center over a 12-week period. Weighted least squares estimation revealed that all three models performed well in terms of fit and were roughly equivalent in terms of their ability to explain behavior. Decomposing the belief structures in the Theory of Planned Behavior provided a moderate increase in the explanation of behavioral intention. Overall, the results indicate that the decomposed Theory of Planned Behavior provides a fuller understanding of behavioral intention by focusing on the factors that are likely to influence systems use through the application of both design and implementation strategies.
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
“Prior research has suggested that employees' perceptions regarding organizational support-that is, facilitating conditions or perceptions of external control (Taylor & Todd, 1995;Venkatesh, 2000;Venkatesh et al., 2003)-will lead to greater user acceptance of new systems.”
From Technology Acceptance Model 3 and a Research Agenda on Interventions (2008) · cites this paper as Taylor & Todd, 1995
In the citing paper
“The fundamental assumption of the theory is that users’ beliefs influence their behavioral intentions, and these intentions, in turn, determine their actual behavior toward using a given technology (Taylor and Todd, 1995).”
From A two-step structural equation modeling and explainable machine learning framework for understanding university students’ adoption of generative AI: balancing intrinsic motivations and perceived risks (2026) · cites this paper as Taylor and Todd, 1995
Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
(1980) · Medical Entomology and Zoology · Cited by 25,810
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
From Intentions to Actions: A Theory of Planned Behavior
Ajzen, I. (1985) · Action Control · doi:10.1007/978-3-642-69746-3_2 · Cited by 19,057
Structural Equations with Latent Variables.
Clogg, C. C., & Bollen, K. A. (1991) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2072165 · Cited by 17,475
Flagged first, then by citations
Cited by
Sorted by citations
Items 601–700 of 1,044
Park, N., Rhoads, M., Hou, J., & Lee, K. M. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.05.048 · Cited by 225
Tarhini, A., Arachchilage, N. A. G., Masa’deh, R. M. T., & Abbasi, M. S. (2015) · International Journal of Technology Diffusion · doi:10.4018/ijtd.2015100104 · Cited by 225
Liébana-Cabanillas, F. J., Muñoz‐Leiva, F., & Sánchez‐Fernández, J. (2017) · Service Business · doi:10.1007/s11628-017-0336-7 · Cited by 209
Examining intention to adopt to internet of things in healthcare technology products
Adem Karahoca, A., Karahoca, D., & Aksöz, M. (2017) · Kybernetes · doi:10.1108/k-02-2017-0045 · Cited by 219
Consumer motives for peer-to-peer sharing
Hawlitschek, F., Teubner, T., & Gimpel, H. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.08.326 · Cited by 219
Impact of demonetization on diffusion of mobile payment service in India
Sobti, N. (2019) · Journal of Advances in Management Research · doi:10.1108/jamr-09-2018-0086 · Cited by 243
Reconceptualizing compatability beliefs in technology acceptance research
Karahanna, E., Agarwal, R., & Angst, C. M. (2006) · MIS Quarterly · doi:10.5555/2017317.2017319 · Cited by 202
(2003) · Journal of the Association for Information Systems · Cited by 202
Kim, J. S. (2016) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-06-2015-0289 · Cited by 218
Plouffe, C. R., Vandenbosch, M., & Hulland, J. (2001) · Journal of Product Innovation Management · doi:10.1016/s0737-6782(00)00072-2 · Cited by 213
User behaviour in QR mobile payment system: the QR Payment Acceptance Model
Liébana-Cabanillas, F. J., de Luna, I. R., & Montoro-Ríos, F. J. (2015) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2015.1047757 · Cited by 213
Reasons associated with preservice teachers’ intention to use immersive virtual reality in education
Bower, M., DeWitt, D., & Lai, J. W. M. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.13009 · Cited by 239
Song, H. J., Ruan, W. J., & Jeon, Y. J. J. (2021) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2021.102943 · Cited by 200
Assessing digital self-efficacy: Review and scale development
Ulfert, A., & Schmidt, I. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104626 · Cited by 308
Rodríguez‐Ardura, I., & Meseguer‐Artola, A. (2015) · Information & Management · doi:10.1016/j.im.2015.11.005 · Cited by 205
Choi, D., Chung, C. Y., Seyha, T., & Young, J. (2020) · Sustainability · doi:10.3390/su12218882 · Cited by 220
Adoption of internet banking services in Gujarat
Patel, K. J., & Patel, H. J. (2017) · International Journal of Bank Marketing · doi:10.1108/ijbm-08-2016-0104 · Cited by 241
Wang, C. (., & Jeong, M. (2018) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2018.04.006 · Cited by 197
Shrivastava, A., Jain, G., Kamble, S., & Belhadi, A. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.123772 · Cited by 197
Picazo-Vela, S., Chou, S. Y., Melcher, A. J., & Pearson, J. M. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.01.005 · Cited by 206
What determines Turkish customers' acceptance of internet banking?
Çelik, H. E. (2008) · International Journal of Bank Marketing · doi:10.1108/02652320810894406 · Cited by 212
Luo, M. M., Chea, S., & Chen, J. (2010) · Decision Support Systems · doi:10.1016/j.dss.2010.11.015 · Cited by 216
Al‐Okaily, M., Lutfi, A., Alsaad, A. K., Taamneh, A. M., & Alsyouf, A. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101367 · Cited by 230
Computer based assessment: Gender differences in perceptions and acceptance
Terzis, V., & Economides, A. A. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.06.005 · Cited by 195
Chen, C.-W. D., & Cheng, C.-Y. (2009) · Behaviour and Information Technology · doi:10.1080/01449290701850111 · Cited by 205
Huang, F., Teo, T. P., Sánchez‐Prieto, J. C., García‐Peñalvo, F. J., & Migueláñéz, S. O. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.01.012 · Cited by 217
Chen, H.-J. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.07.005 · Cited by 206
Sun, Y., Bhattacherjee, A., & Ma, Q. (2009) · Information & Management · doi:10.1016/j.im.2009.06.003 · Cited by 193
Run-hua, X., Frey, R. M., Fleisch, E., & Ilic, A. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.04.011 · Cited by 202
Tommasetti, A., Singer, P., Troisi, O., & Maione, G. (2018) · Sustainability · doi:10.3390/su10072580 · Cited by 204
The Effect of Culture on User Acceptance of Information Technology
Bandyopadhyay, K., & Fraccastoro, K. A. (2007) · Communications of the Association for Information Systems · doi:10.17705/1cais.01923 · Cited by 206
Moons, I., & Pelsmacker, P. D. (2015) · Sustainability · doi:10.3390/su7056212 · Cited by 227
A unified model of knowledge sharing behaviours: theoretical development and empirical test
Chennamaneni, A., Teng, J. T. C., & Raja, M. K. (2011) · Behaviour and Information Technology · doi:10.1080/0144929x.2011.624637 · Cited by 194
Measuring open source software success
Lee, S. T., Kim, H., & Gupta, S. (2007) · Omega · doi:10.1016/j.omega.2007.05.005 · Cited by 191
Curran, J. M., & Meuter, M. L. (2007) · The Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679150401 · Cited by 191
Learner outcomes in an asynchronous distance education environment
Carswell, A. D., & Venkatesh, V. (2002) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.2002.1004 · Cited by 191
Impact of Environmental Uncertainty and Task Characteristics on User Satisfaction with Data
Karimi, J., Somers, T. M., & Gupta, Y. P. (2004) · Information Systems Research · doi:10.1287/isre.1040.0022 · Cited by 193
Development of an instrument to measure the acceptance of Internet technology by consumers
Gardner, C., & Amoroso, D. L. (2004) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2004.1265623 · Cited by 206
Taherdoost, H. (2018) · Behaviour and Information Technology · doi:10.1080/0144929x.2018.1427793 · Cited by 224
Al-Azawei, A., & Alowayr, A. S. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101325 · Cited by 204
An exploration of student internet use in India
Fusilier, M. R., & Durlabhji, S. (2005) · Campus-Wide Information Systems · doi:10.1108/10650740510617539 · Cited by 198
Mobile apps for healthy living: Factors influencing continuance intention for health apps
Yan, M., Filieri, R., Raguseo, E., & Gorton, M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120644 · Cited by 182
Verhagen, T., Feldberg, F., van den Hooff, B., Meents, S., & Merikivi, J. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.10.020 · Cited by 200
Customers’ perspectives regarding e-banking in an emerging economy
Agarwal, R., Rastogi, S., & Mehrotra, A. (2009) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2009.03.002 · Cited by 200
Belanche, D., Flavián, M., & Pérez-Rueda, A. (2020) · Sustainability · doi:10.3390/su12104275 · Cited by 187
Predictors for e‐government adoption in Jordan
Alomari, M. K., Woods, P., & Sandhu, K. (2012) · Information Technology and People · doi:10.1108/09593841211232712 · Cited by 204
Self-Service Technologies and e-Services Risks in Social Commerce Era
Featherman, M. S., & Hajli, N. (2015) · Journal of Business Ethics · doi:10.1007/s10551-015-2614-4 · Cited by 214
Kim, H., Mannino, M. V., & Nieschwietz, R. J. (2009) · International Journal of Accounting Information Systems · doi:10.1016/j.accinf.2009.09.001 · Cited by 202
Cheung, M. F. Y., & To, W. M. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.07.011 · Cited by 196
Lai, Y., Saab, N., & Admiraal, W. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104413 · Cited by 218
A benefit–cost perspective of the consumer adoption of the mobile banking system
Shen, Y., Huang, C., Chu, C., & Hsu, C.-T. (2010) · Behaviour and Information Technology · doi:10.1080/01449290903490658 · Cited by 184
Vishwanath, A., & Goldhaber, G. M. (2003) · New Media & Society · doi:10.1177/146144480354005 · Cited by 184
Benamati, J. ‘., Fuller, M. A., Serva, M. A., & Baroudi, J. J. (2009) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2009.2023111 · Cited by 181
Boonsiritomachai, W., & Pitchayadejanant, K. (2017) · Kasetsart Journal of Social Sciences · doi:10.1016/j.kjss.2017.10.005 · Cited by 184
Theorizing artificial intelligence acceptance and digital entrepreneurship model
Upadhyay, N., Upadhyay, S., & Dwivedi, Y. K. (2021) · International Journal of Entrepreneurial Behaviour & Research · doi:10.1108/ijebr-01-2021-0052 · Cited by 206
USER ACCEPTANCE OF VIRTUAL WORLDS
Fetscherin, M., & Lattemann, C. (2008) · Cited by 184
A field study of the adoption of software process innovations by information systems professionals
Agarwal, R., & Prasad, J. (2000) · IEEE Transactions on Engineering Management · doi:10.1109/17.865899 · Cited by 182
Kohnke, A., Cole, M. L., & Bush, R. (2014) · Journal of technology management & innovation · doi:10.4067/s0718-27242014000200003 · Cited by 181
Gender Differences in Perceptions and Use of Communication Technologies
Ilie, V., Slyke, C. V., Green, G., & Lou, H. (2005) · Information Resources Management Journal · doi:10.4018/irmj.2005070102 · Cited by 186
Understanding intention to continuously share information on weblogs
Lu, H., & Hsiao, K. (2007) · Internet Research · doi:10.1108/10662240710828030 · Cited by 180
Hsieh, J. J. P.-A., Rai, A., & Keil, M. (2010) · Information Systems Research · doi:10.1287/isre.1090.0256 · Cited by 178
Yang, S., Carlson, J. R., & Chen, S. (2019) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.102020 · Cited by 197
Consumer adoption of m-banking: a behavioral reasoning theory perspective
Gupta, A., & Arora, N. (2017) · International Journal of Bank Marketing · doi:10.1108/ijbm-11-2016-0162 · Cited by 191
Big data management in healthcare: Adoption challenges and implications
Chen, P.-T., Lin, C.-L., & Wu, W.-N. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102078 · Cited by 178
Characterizing Chinese consumers’ intention to use live e-commerce shopping
Zhou, M., Huang, J., Wu, K., Huang, X., Kong, N., & Campy, K. S. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101767 · Cited by 210
Toward a better understanding of behavioral intention and system usage constructs
Wu, J., & Du, H. (2012) · European Journal of Information Systems · doi:10.1057/ejis.2012.15 · Cited by 175
Comparing theories to explain e-commerce adoption
Grandón, E. E., Nasco, S. A., & Mykytyn, P. P. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2009.11.015 · Cited by 177
The Influence of Values on E-learning Adoption
Mehta, A., Morris, N. P., Swinnerton, B. J., & Homer, M. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103617 · Cited by 214
Investigating end-user acceptance of autonomous electric buses to accelerate diffusion
Herrenkind, B., Brendel, B., Nastjuk, I., Greve, M., & Kolbe, L. M. (2019) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2019.08.003 · Cited by 195
Consumer adoption of smartphone fitness apps: an extended UTAUT2 perspective
Dhiman, N., Arora, N., Dogra, N., & Gupta, A. (2019) · Journal of Indian Business Research · doi:10.1108/jibr-05-2018-0158 · Cited by 209
An empirical investigation of anti-spyware software adoption: A multitheoretical perspective
Lee, Y., & Kozar, K. A. (2008) · Information & Management · doi:10.1016/j.im.2008.01.002 · Cited by 177
Tsai, H.-T., Huang, H., Jaw, Y., & Chen, W.-K. (2006) · Psychology and Marketing · doi:10.1002/mar.20121 · Cited by 176
Identifying factors influencing consumers’ intent to install mobile applications
Harris, M. A., Brookshire, R. G., & Chin, A. G. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.02.004 · Cited by 180
WHO'S AFRAID OF THE VIRTUAL WORLD? Anxiety and Computer-Mediated Communication
Brown, S. A., Fuller, R. M., & Vician, C. M. (2004) · Journal of the Association for Information Systems · doi:10.17705/1jais.00046 · Cited by 177
Uncovering the dark side of gamification at work: Impacts on engagement and well-being
Hammedi, W., Leclercq, T., Poncin, I., & Alkire, L. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.032 · Cited by 213
Adoption of digital banking channels in an emerging economy: exploring the role of in-branch efforts
Kaur, S. J., Ali, L., Hassan, M. K., & Al-Emran, M. (2021) · Journal of Financial Services Marketing · doi:10.1057/s41264-020-00082-w · Cited by 236
de Luna, I. R., Montoro-Ríos, F. J., & Liébana-Cabanillas, F. J. (2015) · Information Systems and e-Business Management · doi:10.1007/s10257-015-0284-5 · Cited by 179
Lu, C.-S., Lai, K., & Cheng, T. C. E. (2007) · European Journal of Operational Research · doi:10.1016/j.ejor.2006.05.001 · Cited by 201
Mediating the impact of technology usage on perceived ease of use by anxiety
Saadé, R. G., & Kira, D. (2006) · Computers & Education · doi:10.1016/j.compedu.2006.01.009 · Cited by 196
Toward a model for the acceptance of Internet banking in developing countries
Sukkar, A. A., & Hasan, H. M. (2005) · Information Technology for Development · doi:10.1002/itdj.20026 · Cited by 179
Dutta, B., & Hwang, H. (2021) · Sustainability · doi:10.3390/su132112025 · Cited by 175
“Security begins at home”: Determinants of home computer and mobile device security behavior
Thompson, N., McGill, T. J., & Wang, X. (2017) · Computers & Security · doi:10.1016/j.cose.2017.07.003 · Cited by 174
Teng, Z., Cai, Y., Gao, Y., Zhang, X., & Li, X. (2022) · Mobile Information Systems · doi:10.1155/2022/5479215 · Cited by 206
Why people buy virtual items in virtual worlds with real money
Guo, Y., & Barnes, S. J. (2007) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1314234.1314247 · Cited by 180
An Examination of the Technology Acceptance Model in Uruguay and the US: A Focus on Culture
McCoy, S., Everard, A., & Jones, B. (2005) · Journal of Global Information Technology Management · doi:10.1080/1097198x.2005.10856395 · Cited by 173
Analyzing the impact of consumer innovativeness and perceived risk in internet banking adoption
Chauhan, V., Yadav, R., & Choudhary, V. (2019) · International Journal of Bank Marketing · doi:10.1108/ijbm-02-2018-0028 · Cited by 183
Predicting knowledge sharing practices through intention: A test of competing models
Kuo, F., & Young, M. (2008) · Computers in Human Behavior · doi:10.1016/j.chb.2008.03.015 · Cited by 172
Antecedents of continuance intentions towards e‐shopping: the case of Saudi Arabia
Al-maghrabi, T., Dennis, C., & Halliday, S. V. (2010) · Journal of Enterprise Information Management · doi:10.1108/17410391111097447 · Cited by 179
Organizational adoption of enterprise resource planning systems: A conceptual framework
Başoğlu, N., Daim, T. U., & Kerimoglu, O. (2007) · The Journal of High Technology Management Research · doi:10.1016/j.hitech.2007.03.005 · Cited by 181
Chauhan, S., & Jaiswal, M. (2016) · The International Journal of Management Education · doi:10.1016/j.ijme.2016.05.005 · Cited by 180
Understanding Online Banking Adoption in a Developing Country
Khan, I. U., Hameed, Z., & Khan, S. U. (2016) · Journal of Global Information Management · doi:10.4018/jgim.2017010103 · Cited by 172
Çalışır, F., Gümüşsoy, Ç. A., Bayraktaroglu, A. E., & Karaali, D. (2014) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20548 · Cited by 196
An integrated model of factors affecting consumer attitudes towards online shopping
Akroush, M. N., & Al‐Debei, M. M. (2015) · Business Process Management Journal · doi:10.1108/bpmj-02-2015-0022 · Cited by 181
Chiu, J. L., Bool, N. C., & Chiu, C. L. (2017) · Asia Pacific Journal of Innovation and Entrepreneurship · doi:10.1108/apjie-08-2017-029 · Cited by 185
Yang, H., Song, H., Cheung, C., & Guan, J. (2021) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2021.103000 · Cited by 200
Clercq, D. D., & Rius, I. B. (2007) · Journal of Small Business Management · doi:10.1111/j.1540-627x.2007.00223.x · Cited by 170
Learning Online Social Support: An Investigation of Network Information Technology Based on UTAUT
Lin, C., & Bhattacherjee, A. (2008) · CyberPsychology & Behavior · doi:10.1089/cpb.2007.0057 · Cited by 169
Factors affecting e-commerce adoption among SMEs in Ghana
Awiagah, R., Kang, J., & Lim, J. I. (2015) · Information Development · doi:10.1177/0266666915571427 · Cited by 215
Zhao, F., Ahmed, F., & Faraz, N. A. (2020) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2020.103725 · Cited by 196
Kim, Y., & Stanton, J. M. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23424 · Cited by 168
Metadata
- Authors
- Taylor, S., & Todd, P. A.
- Affiliations
- Queen's University (CA)
- Venue
- Information Systems Research
- Published
- 1995-06
- Volume
- 6
- Issue
- 2
- Pages
- 144-176
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W1987198869
- Cited by
- 8,815
- References
- 52
- Citations by year
- 2026: 226 · 2025: 285 · 2024: 376 · 2023: 421 · 2022: 485 · 2021: 558 · 2020: 448 · 2019: 422 · 2018: 428 · 2017: 357 · 2016: 384 · 2015: 481 · 2014: 453 · 2013: 487 · 2012: 410
- FWCI
- 53.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- information technology use, technology acceptance model, theory of planned behavior, behavioral intention, student users, belief structures, model comparison
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