Reference health
Array programming with NumPy
35/35 checkable references clean · checked 2026-07-24
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
22 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 35 checked references that resolve
resolves10.1103/PhysRevLett.116.061102
Observation of Gravitational Waves from a Binary Black Hole Merger
resolves10.3847/0004-637X/829/1/11
HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE
resolves10.1038/s41592-019-0686-2
SciPy 1.0: fundamental algorithms for scientific computing in Python
resolves10.1109/ICPADS.2012.97
Model-driven Level 3 BLAS Performance Optimization on Loongson 3A Processor
resolves10.3847/1538-3881/aac387
Binary Companions of Evolved Stars in APOGEE DR14: Search Method and Catalog of ∼5000 Companions
resolves10.1093/bioinformatics/btp163
Biopython: freely available Python tools for computational molecular biology and bioinformatics
resolves10.1109/MCSE.2006.122
Software Carpentry: Getting Scientists to Write Better Code by Making Them More Productive
resolves10.1088/1749-4680/8/1/014001
Pythran: enabling static optimization of scientific Python programs
The 22 references without a DOI — listed, not checked
no DOI — not checkedAscher, D., Dubois, P. F., Hinsen, K., Hugunin, J. & Oliphant, T. E. An Open Source Project: Numerical Python (Lawrence Livermore National Laboratory, 2001).
no DOI — not checkedYang, T.-Y., Furnish, G. & Dubois, P. F. Steering object-oriented scientific computations. In Proc. TOOLS USA 97. Intl Conf. Technology of Object Oriented Systems and Languages (eds Ege, R., Singh, M. & Meyer, B.) 112–119 (IEEE, 1997).
no DOI — not checkedGreenfield, P., Miller, J. T., Hsu, J. & White, R. L. numarray: a new scientific array package for Python. In PyCon DC 2003 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.112.9899 (2003).
no DOI — not checkedOliphant, T. E. Guide to NumPy 1st edn (Trelgol Publishing, 2006).
no DOI — not checkedPedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
no DOI — not checkedKluyver, T. et al. Jupyter Notebooks—a publishing format for reproducible computational workflows. In Positioning and Power in Academic Publishing: Players, Agents and Agendas (eds Loizides, F. & Schmidt, B.) 87–90 (IOS Press, 2016).
no DOI — not checkedHagberg, A. A., Schult, D. A. & Swart, P. J. Exploring network structure, dynamics, and function using NetworkX. In Proc. 7th Python in Science Conf. (eds Varoquaux, G., Vaught, T. & Millman, K. J.) 11–15 (2008).
no DOI — not checkedHamman, J., Rocklin, M. & Abernathy, R. Pangeo: a big-data ecosystem for scalable Earth system science. In EGU General Assembly Conf. Abstracts 12146 (2018).
no DOI — not checkedChael, A. A. et al. ehtim: imaging, analysis, and simulation software for radio interferometry. Astrophysics Source Code Library https://ascl.net/1904.004 (2019).
no DOI — not checkedvan der Walt, S. The SciPy Documentation Project (technical overview). In Proc. 7th Python in Science Conf. (SciPy 2008) (eds Varoquaux, G., Vaught, T. & Millman, K. J.) 27–28 (2008).
no DOI — not checkedHarrington, J. The SciPy Documentation Project. In Proc. 7th Python in Science Conference (SciPy 2008) (eds Varoquaux, G., Vaught, T. & Millman, K. J.) 33–35 (2008).
no DOI — not checkedHarrington, J. & Goldsmith, D. Progress report: NumPy and SciPy documentation in 2009. In Proc. 8th Python in Science Conf. (SciPy 2009) (eds Varoquaux, G., van der Walt, S. & Millman, K. J.) 84–87 (2009).
no DOI — not checkedRoyal Astronomical Society Report of the RAS ‘A’ Awards Committee 2020: Astropy Project: 2020 Group Achievement Award (A) https://ras.ac.uk/sites/default/files/2020-01/Group%20Award%20-%20Astropy.pdf (2020).
no DOI — not checkedPaszke, A. et al. Pytorch: an imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems 32 (eds Wallach, H. et al.) 8024–8035 (Neural Information Processing Systems, 2019).
no DOI — not checkedAbadi, M. et al. TensorFlow: a system for large-scale machine learning. In OSDI’16: Proc. 12th USENIX Conf. Operating Systems Design and Implementation (chairs Keeton, K. & Roscoe, T.) 265–283 (USENIX Association, 2016).
no DOI — not checkedChen, T. et al. MXNet: a flexible and efficient machine learning library for heterogeneous distributed systems. Preprint at http://www.arxiv.org/abs/1512.01274 (2015).
no DOI — not checkedEntschev, P. Distributed multi-GPU computing with Dask, CuPy and RAPIDS. In EuroPython 2019 https://ep2019.europython.eu/media/conference/slides/fX8dJsD-distributed-multi-gpu-computing-with-dask-cupy-and-rapids.pdf (2019).
no DOI — not checkedBarrett, K. A., Chiu, Y. H., Painter, J. F., Motteler, Z. C. & Dubois, P. F. Basis System, Part I: Running a Basis Program—A Tutorial for Beginners UCRL-MA-118543, Vol. 1 (Lawrence Livermore National Laboratory 1995).
no DOI — not checkedDubois, P. F. & Motteler, Z. Basis System, Part II: Basis Language Reference Manual UCRL-MA-118543, Vol. 2 (Lawrence Livermore National Laboratory, 1995).
no DOI — not checkedChiu, Y. H. & Dubois, P. F. Basis System, Part III: EZN User Manual UCRL-MA-118543, Vol. 3 (Lawrence Livermore National Laboratory, 1995).
no DOI — not checkedChiu, Y. H. & Dubois, P. F. Basis System, Part IV: EZD User Manual UCRL-MA-118543, Vol. 4 (Lawrence Livermore National Laboratory, 1995).
no DOI — not checkedLattner, C. & Adve, V. LLVM: a compilation framework for lifelong program analysis and transformation. In Proc. 2004 Intl Symp. Code Generation and Optimization (CGO’04) 75–88 (IEEE, 2004).
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work were clean at the dated check: each resolved to a known work in a public registry, and none
carried a retraction notice at that time. It says nothing about the quality, findings,
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