Jungfraujoch is developed at one facility, so the reader and the reduction pipeline are exercised on data collected elsewhere - other detectors, other file formats, other conventions. That data was collected and published by other people, and until now nothing in the repository said so. NON_SLS_TEST_DATA lists all 51 datasets: the DOI to cite for each, the repository it came from, and the experiment as deposited. Beamline, resolution, space group and cell are the values deposited with the corresponding PDB entry, read from the RCSB data API - not results measured here; no quantity produced by this software appears on the page. The detector is read out of the image file instead, because the detector named in a PDB entry is often only approximate, and the twelve cases where the two disagree are listed rather than silently reconciled. ACKNOWLEDGEMENT gains a section for the repositories themselves, with the IRRMC, SBGrid and Zenodo citations and the PDB citation for the metadata. Every DOI on both pages was resolved before it was written down. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Lc5JG6kJqZoCWaoZ43JGTW
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# Acknowledgements
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Citation: F. Leonarski, M. Bruckner, C. Lopez-Cuenca, A. Mozzanica, H.-C. Stadler, Z. Matej, A. Castellane, B. Mesnet, J. Wojdyla, B. Schmitt and M. Wang "Jungfraujoch: hardware-accelerated data-acquisition system for kilohertz pixel-array X-ray detectors" (2023), J. Synchrotron Rad., 30, 227-234 [doi:10.1107/S1600577522010268](https://doi.org/10.1107/S1600577522010268).
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The project is supported by :
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* Innosuisse via Innovation Project "NextGenDCU high data rate acquisition system for X-ray detectors in structural biology applications" (101.535.1 IP-ENG; Apr 2023 - Sep 2025).
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* ETH Domain via Open Research Data Contribute project (Jan - Dec 2023)
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* AMD University Program with donation of licenses of Ethernet IP cores and Vivado software
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Decoding bitshuffle+LZ4 images on the GPU, rather than decompressing them on the host and uploading
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the result, follows Jon Wright (ESRF): "Experiences with GPU decompression for bitshuffle + LZ4
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data", HDF5 User Group meeting (2021), and [bslz4decoders](https://github.com/jonwright/bslz4decoders).
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The CUDA kernels in Jungfraujoch are its own, but the approach is his.
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Spot extraction groups strong pixels into spots with the sparse connected-component labelling of the
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ACTS traccc project: P. Gessinger, H. M. Gray, A. Krasznahorkay, C. Leggett, J. Niermann,
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A. Salzburger, S. N. Swatman and B. Yeo, "traccc: GPU track reconstruction library for HEP
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experiments" (2025), [arXiv:2505.22822](https://arxiv.org/abs/2505.22822);
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[traccc](https://github.com/acts-project/traccc). The CPU spot extractor adapts its SparseCCL source,
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and the CUDA spot extractor follows the design of its GPU counterpart - a backward-neighbour graph
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over a sorted hit list, resolved by a parallel union-find. traccc is MPL-2.0; see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md).
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This software uses Viridis, Magma and Inferno colormaps from Matplotlib under its BSD-compatible license
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## Public diffraction data used for testing
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Jungfraujoch is developed at the Swiss Light Source, so it is tested against diffraction data
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collected at other facilities, on detectors and in file formats we do not produce ourselves. That
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data was collected and published by other people. Every dataset used, the DOI to cite for it, and
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the deposition it belongs to are listed in [NON_SLS_TEST_DATA](NON_SLS_TEST_DATA.md); we thank the
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depositors, and the repositories that make the data findable and citable.
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**[IRRMC](https://proteindiffraction.org/)**, the Integrated Resource for Reproducibility in
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Macromolecular Crystallography (Minor lab, University of Virginia), is the source of most of them.
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IRRMC releases its data under CC0 and asks that the DOI of the dataset be cited; those DOIs are in
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the table. M. Grabowski, K. M. Langner, M. Cymborowski, P. J. Porebski, P. Sroka, H. Zheng,
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D. R. Cooper, M. D. Zimmerman, M.-A. Elsliger, S. K. Burley and W. Minor, "A public database of
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macromolecular diffraction experiments" (2016), Acta Cryst. D72, 1181-1193
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[doi:10.1107/S2059798316014716](https://doi.org/10.1107/S2059798316014716); M. Grabowski,
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M. Cymborowski, P. J. Porebski, T. Osinski, I. G. Shabalin, D. R. Cooper and W. Minor, "The
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Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first
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four years" (2019), Struct. Dyn. 6, 064301
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[doi:10.1063/1.5128672](https://doi.org/10.1063/1.5128672).
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**[SBGrid Data Bank](https://data.sbgrid.org/)** supplied five of the datasets. P. A. Meyer,
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S. Socias, J. Key, E. Ransey, E. C. Tjon, A. Buschiazzo et al., "Data publication with the
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structural biology data grid supports live analysis" (2016), Nat. Commun. 7, 10882
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[doi:10.1038/ncomms10882](https://doi.org/10.1038/ncomms10882).
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**[Zenodo](https://zenodo.org/)** hosts seven, deposited there directly by the groups that
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collected them. European Organization for Nuclear Research and OpenAIRE, "Zenodo" (2013), CERN
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[doi:10.25495/7GXK-RD71](https://doi.org/10.25495/7GXK-RD71).
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The beamline, resolution, space group and unit cell quoted for each dataset are the values
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deposited with the corresponding PDB entry, read from the RCSB PDB data API. H. M. Berman,
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J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov and P. E. Bourne,
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"The Protein Data Bank" (2000), Nucleic Acids Res. 28, 235-242
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[doi:10.1093/nar/28.1.235](https://doi.org/10.1093/nar/28.1.235).
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## Crystallographic methods adopted from other packages
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The analysis pipeline reimplements methods first published, and in most cases first implemented, by
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other crystallographic software. The code below is Jungfraujoch's own; the methods are theirs, and
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are acknowledged here. Where a package's source was consulted this is said explicitly. None of these
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packages is linked or vendored, with the single exception of GEMMI (see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)).
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**[XDS](https://xds.mr.mpg.de/)** — rotation geometry and notation, the reciprocal Lorentz and
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partiality treatment, the maximum-likelihood mosaicity estimate, the `MINPK` criterion for rejecting
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a reflection whose predicted profile is not cleanly its own, the intensity-based test for a
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centred lattice, and the scaling correction surfaces indexed by image number and detector region. W. Kabsch, "XDS" (2010), Acta Cryst. D66, 125-132
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[doi:10.1107/S0907444909047337](https://doi.org/10.1107/S0907444909047337); W. Kabsch, "Integration,
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scaling, space-group assignment and post-refinement" (2010), Acta Cryst. D66, 133-144
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[doi:10.1107/S0907444909047374](https://doi.org/10.1107/S0907444909047374).
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**Profile fitting** with reweighted, de-biased variances is the Kabsch/Otwinowski iteration, from the
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second XDS paper above and from Z. Otwinowski and W. Minor, "Processing of X-ray diffraction data
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collected in oscillation mode" (1997), Methods Enzymol. 276, 307-326
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[doi:10.1016/S0076-6879(97)76066-X](https://doi.org/10.1016/S0076-6879%2897%2976066-X).
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**[DIALS](https://dials.github.io/)** — the resolution cutoff from the CC1/2 fall-off, per-observation
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outlier rejection at merge, the scaling error model, and the treatment of a reflection whose
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background is contaminated. Its published behaviour, and in places its source, settled several
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choices here. G. Winter, D. G. Waterman, J. M. Parkhurst et al., "DIALS: implementation and
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evaluation of a new integration package" (2018), Acta Cryst. D74, 85-97
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[doi:10.1107/S2059798317017235](https://doi.org/10.1107/S2059798317017235); D. G. Waterman,
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G. Winter, R. J. Gildea et al., "Diffraction-geometry refinement in the DIALS framework" (2016),
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Acta Cryst. D72, 558-575 [doi:10.1107/S2059798316002187](https://doi.org/10.1107/S2059798316002187);
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J. Beilsten-Edmands, G. Winter, R. Gildea et al., "Scaling diffraction data in the DIALS software
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package: algorithms and new approaches for multi-crystal scaling" (2020), Acta Cryst. D76, 385-399
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[doi:10.1107/S2059798320003198](https://doi.org/10.1107/S2059798320003198); J. M. Parkhurst,
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G. Winter, D. G. Waterman et al., "Robust background modelling in DIALS" (2016), J. Appl. Cryst. 49,
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1912-1921 [doi:10.1107/S1600576716013595](https://doi.org/10.1107/S1600576716013595).
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**[POINTLESS](https://www.ccp4.ac.uk/)** (CCP4) — the space-group search. Stage A scores each
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candidate rotation operator by the correlation of I(h) with I(Rh) on **resolution-normalised**
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intensities (E²), as POINTLESS does — both arms of a symmetry pair sit at the same |s|, so on raw
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intensities the resolution fall-off is variance shared between them and lifts a false operator's
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correlation as much as a true one's; the screw-axis test scores a
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predicted-absent class against the rest of its own axial row rather than against a global mean or a
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fixed cut, and lets confidence fall away with the number of axial reflections instead of refusing
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below a count. P. Evans, "Scaling and assessment of data quality" (2006), Acta Cryst. D62, 72-82
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[doi:10.1107/S0907444905036693](https://doi.org/10.1107/S0907444905036693); P. R. Evans, "An
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introduction to data reduction: space-group determination, scaling and intensity statistics" (2011),
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Acta Cryst. D67, 282-292 [doi:10.1107/S090744491003982X](https://doi.org/10.1107/S090744491003982X);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061);
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J. Agirre, M. Atanasova, H. Bagdonas et al., "The CCP4 suite: integrative software for macromolecular
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crystallography" (2023), Acta Cryst. D79, 449-461
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[doi:10.1107/S2059798323003595](https://doi.org/10.1107/S2059798323003595).
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**[MOSFLM](https://www.mrc-lmb.cam.ac.uk/mosflm/)** — the Rossmann FFT autoindexing algorithm and
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post-refinement practice, including which parameters are safe to refine per image and which must be
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refined over a wedge. A. G. W. Leslie and H. R. Powell, "Processing diffraction data with MOSFLM"
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(2007), in *Evolving Methods for Macromolecular Crystallography*, NATO Science Series II, vol. 245,
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41-51 [doi:10.1007/978-1-4020-6316-9_4](https://doi.org/10.1007/978-1-4020-6316-9_4);
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T. G. G. Battye, L. Kontogiannis, O. Johnson, H. R. Powell and A. G. W. Leslie, "iMOSFLM: a new
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graphical interface for diffraction-image processing with MOSFLM" (2011), Acta Cryst. D67, 271-281
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[doi:10.1107/S0907444910048675](https://doi.org/10.1107/S0907444910048675); H. R. Powell,
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T. G. G. Battye, L. Kontogiannis, O. Johnson and A. G. W. Leslie, "Integrating macromolecular X-ray
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diffraction data with the graphical user interface iMosflm" (2017), Nat. Protoc. 12, 1310-1325
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[doi:10.1038/nprot.2017.037](https://doi.org/10.1038/nprot.2017.037).
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**[CrystFEL](https://www.desy.de/~twhite/crystfel/)** — spot finding, the three-ring integration
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region, the serial/stills processing model, and the per-frame indexing acceptance test
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(`indexing_peak_check()` in `peaks.c`). T. A. White, R. A. Kirian, A. V. Martin, A. Aquila, K. Nass,
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A. Barty and H. N. Chapman, "CrystFEL: a software suite for snapshot serial crystallography" (2012),
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J. Appl. Cryst. 45, 335-341 [doi:10.1107/S0021889812002312](https://doi.org/10.1107/S0021889812002312).
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**[GEMMI](https://github.com/project-gemmi/gemmi)** — symmetry operations, unit-cell and
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structure-factor machinery, and MTZ / XDS_ASCII I/O. Vendored in `gemmi_gph/`, so it also carries a
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licence obligation. M. Wojdyr, "GEMMI: A library for structural biology" (2022), J. Open Source
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Softw. 7, 4200 [doi:10.21105/joss.04200](https://doi.org/10.21105/joss.04200).
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**Hexagonal-ice ring positions** — the eleven ring $d$ spacings from 3.895 to 1.522 Å that the
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ice-ring score, the ice-ring flagging and the ice calibrant are all built on are taken from the
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measurements of, not enumerated from a cell. D. W. Moreau, H. Atakisi and R. E. Thorne, "Ice in
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biomolecular cryocrystallography" (2021), Acta Cryst. D77, 540-554
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[doi:10.1107/S2059798321001170](https://doi.org/10.1107/S2059798321001170).
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That list ends at 1.522 Å by its own scope, so the eight bands below it are calculated here rather
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than taken from anyone: ice Ih structure factors on the oxygen sublattice, kept where they reach 3% of
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the strongest line, which reproduces the eleven measured positions exactly. The lattice constants are
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Röttger and co-workers'. A. Röttger, A. Endriss, J. Ihringer, S. Doyle and W. F. Kuhs, "Lattice
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constants and thermal expansion of H2O and D2O ice Ih between 10 and 265 K" (1994), Acta Cryst. B50,
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644-648 [doi:10.1107/S0108768194004933](https://doi.org/10.1107/S0108768194004933).
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**Diffraction anisotropy** — the description of the overall fall-off by a single anisotropic
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displacement tensor, its symmetry constraints, and the fact that only its deviatoric part is
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determined (the isotropic part being degenerate with the overall scale) are Sheriff and Hendrickson's.
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The estimator fits that tensor to the observed intensity distribution, taking sigma(I) into account,
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in the sense of Popov and Bourenkov. The directional diffraction limits - <I/sigma(I)> in a cone about
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each principal direction, and the reporting of the anisotropic deltaB as the range of the principal
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components - follow AIMLESS. rugnux reports these; it corrects no intensity and removes no reflection
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on a directional criterion. S. Sheriff and W. A. Hendrickson, "Description of overall anisotropy in
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diffraction from macromolecular crystals" (1987), Acta Cryst. A43, 118-121
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[doi:10.1107/S010876738709977X](https://doi.org/10.1107/S010876738709977X); A. N. Popov and
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G. P. Bourenkov, "Choice of data-collection parameters based on statistic modelling" (2003), Acta
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Cryst. D59, 1145-1153 [doi:10.1107/S0907444903008163](https://doi.org/10.1107/S0907444903008163);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061).
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**[ANODE](https://doi.org/10.1107/S0021889811041768)** — reading the anomalous difference map at the
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atoms of a supplied model and reporting the strongest sites by name, instead of searching the map for
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blobs. The map itself is the textbook anomalous difference Fourier; what is taken from ANODE is that
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reading: A. Thorn and G. M. Sheldrick, "ANODE: anomalous and heavy-atom density calculation" (2011),
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J. Appl. Cryst. 44, 1285-1287
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[doi:10.1107/S0021889811041768](https://doi.org/10.1107/S0021889811041768).
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**Data-quality statistics** follow the established conventions rather than any one program: R_meas
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and R_pim, CC1/2 and CC\*, and the reporting of I/sigma(I). K. Diederichs and P. A. Karplus, "Improved
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R-factors for diffraction data analysis in macromolecular crystallography" (1997), Nat. Struct. Biol.
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4, 269-275 [doi:10.1038/nsb0497-269](https://doi.org/10.1038/nsb0497-269); P. A. Karplus and
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K. Diederichs, "Linking crystallographic model and data quality" (2012), Science 336, 1030-1033
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[doi:10.1126/science.1218231](https://doi.org/10.1126/science.1218231); K. Diederichs and
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P. A. Karplus, "Better models by discarding data?" (2013), Acta Cryst. D69, 1215-1222
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[doi:10.1107/S0907444913001121](https://doi.org/10.1107/S0907444913001121).
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**Uncertainty conventions** follow the IUCr Commission on Crystallographic Nomenclature:
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D. Schwarzenbach, S. C. Abrahams, H. D. Flack et al., "Statistical descriptors in crystallography:
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Report of the IUCr Subcommittee on Statistical Descriptors" (1989), Acta Cryst. A45, 63-75
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[doi:10.1107/S0108767388009596](https://doi.org/10.1107/S0108767388009596); D. Schwarzenbach,
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S. C. Abrahams, H. D. Flack, E. Prince and A. J. C. Wilson, "Statistical descriptors in
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crystallography. II. Report of a Working Group on Expression of Uncertainty in Measurement" (1995),
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Acta Cryst. A51, 565-569 [doi:10.1107/S0108767395002340](https://doi.org/10.1107/S0108767395002340).
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