The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
BAGEL: Brilliantly Advanced General Electronic‐structure Library
Open accessAbstract
On behalf of the development team, I review the capabilities of the Brilliantly Advanced General Electronic‐structure Library (BAGEL) program package in this article. BAGEL is a newly developed full‐fledged program package for electronic‐structure computation in quantum chemistry, which is released under the GNU General Public License with many contributions from the developers. The unique features include analytical CASPT2 nuclear energy gradients and derivative couplings, relativistic multireference wave functions based on the Dirac equation, and implementations of novel electronic structure theories. All of the programs are efficiently parallelized using both threads and MPI processes. We also discuss the code generator SMITH3, which has been used to implement some of the programs in BAGEL. The developers’ contributions are listed at the end of the main text. WIREs Comput Mol Sci 2018, 8:e1331. doi: 10.1002/wcms.1331 This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods
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
The Density Matrix Renormalization Group in Quantum Chemistry
Chan, G. K.-L., & Sharma, S. (2011) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-032210-103338 · Cited by 822
Cited by
OpenMolcas: From Source Code to Insight
Fdez. Galván, I., Vacher, M., Alavi, A., Angeli, C., Aquilante, F., Autschbach, J., Bao, J. J., Bokarev, S. I., Bogdanov, N. A., Carlson, R. K., et al. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00532 · Cited by 1,114
Multireference Electron Correlation Methods: Journeys along Potential Energy Surfaces
Park, J. W., Al-Saadon, R., MacLeod, M. K., Shiozaki, T., & Vlaisavljevich, B. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00496 · Cited by 155
Self-citationThe Shape of Full Configuration Interaction to Come
Eriksen, J. J. (2021) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.0c03225 · Cited by 66
Metadata
- Authors
- Shiozaki, T.
- Venue
- WIREs Computational Molecular Science
- Publisher
- Wiley
- Published
- 2017-08-29
- Volume
- 8
- Issue
- 1
- ISSN
- 1759-0876 (ISSN-L)
- 1759-0884
- OpenAlex
- W2735018448
- Cited by
- 237
- References
- 1
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- green
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.