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- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Gilmore, G., et al.
(författare)
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The Gaia-ESO Public Spectroscopic Survey : Motivation, implementation, GIRAFFE data processing, analysis, and final data products star
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 666
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Tidskriftsartikel (refereegranskat)abstract
- Context. The Gaia-ESO Public Spectroscopic Survey is an ambitious project designed to obtain astrophysical parameters and elemental abundances for 100 000 stars, including large representative samples of the stellar populations in the Galaxy, and a well-defined sample of 60 (plus 20 archive) open clusters. We provide internally consistent results calibrated on benchmark stars and star clusters, extending across a very wide range of abundances and ages. This provides a legacy data set of intrinsic value, and equally a large wide-ranging dataset that is of value for the homogenisation of other and future stellar surveys and Gaia's astrophysical parameters. Aims. This article provides an overview of the survey methodology, the scientific aims, and the implementation, including a description of the data processing for the GIRAFFE spectra. A companion paper introduces the survey results. Methods. Gaia-ESO aspires to quantify both random and systematic contributions to measurement uncertainties. Thus, all available spectroscopic analysis techniques are utilised, each spectrum being analysed by up to several different analysis pipelines, with considerable effort being made to homogenise and calibrate the resulting parameters. We describe here the sequence of activities up to delivery of processed data products to the ESO Science Archive Facility for open use. Results. The Gaia-ESO Survey obtained 202 000 spectra of 115 000 stars using 340 allocated VLT nights between December 2011 and January 2018 from GIRAFFE and UVES. Conclusions. The full consistently reduced final data set of spectra was released through the ESO Science Archive Facility in late 2020, with the full astrophysical parameters sets following in 2022. A companion article reviews the survey implementation, scientific highlights, the open cluster survey, and data products.
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- Randich, S., et al.
(författare)
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The Gaia-ESO Public Spectroscopic Survey : Implementation, data products, open cluster survey, science, and legacy
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP SCIENCES S A. - 0004-6361 .- 1432-0746. ; 666
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Tidskriftsartikel (refereegranskat)abstract
- Context. In the last 15 years different ground-based spectroscopic surveys have been started (and completed) with the general aim of delivering stellar parameters and elemental abundances for large samples of Galactic stars, complementing Gaia astrometry. Among those surveys, the Gaia-ESO Public Spectroscopic Survey, the only one performed on a 8m class telescope, was designed to target 100 000 stars using FLAMES on the ESO VLT (both Giraffe and UVES spectrographs), covering all the Milky Way populations, with a special focus on open star clusters. Aims. This article provides an overview of the survey implementation (observations, data quality, analysis and its success, data products, and releases), of the open cluster survey, of the science results and potential, and of the survey legacy. A companion article reviews the overall survey motivation, strategy, Giraffe pipeline data reduction, organisation, and workflow. Methods. We made use of the information recorded and archived in the observing blocks; during the observing runs; in a number of relevant documents; in the spectra and master catalogue of spectra; in the parameters delivered by the analysis nodes and the working groups; in the final catalogue; and in the science papers. Based on these sources, we critically analyse and discuss the output and products of the Survey, including science highlights. We also determined the average metallicities of the open clusters observed as science targets and of a sample of clusters whose spectra were retrieved from the ESO archive. Results. The Gaia-ESO Survey has determined homogeneous good-quality radial velocities and stellar parameters for a large fraction of its more than 110 000 unique target stars. Elemental abundances were derived for up to 31 elements for targets observed with UVES. Lithium abundances are delivered for about 1/3 of the sample. The analysis and homogenisation strategies have proven to be successful; several science topics have been addressed by the Gaia-ESO consortium and the community, with many highlight results achieved. Conclusions. The final catalogue will be released through the ESO archive in the first half of 2022, including the complete set of advanced data products. In addition to these results, the Gaia-ESO Survey will leave a very important legacy, for several aspects and for many years to come.
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- Awes, T., et al.
(författare)
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Design and performance of a silicon–tungsten calorimeter prototype module and the associated readout
- 2021
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Ingår i: Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. - : Elsevier BV. - 0168-9002. ; 988
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Tidskriftsartikel (refereegranskat)abstract
- We describe the details of a silicon–tungsten prototype electromagnetic calorimeter module and associated readout electronics. Detector performance for this prototype has been measured in test beam experiments at the CERN PS and SPS accelerator facilities in 2015/16. The results are compared to those in Monte Carlo Geant4 simulations. This is the first real-world demonstration of the performance of a custom ASIC designed for fast, lower-power, high-granularity applications.
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- Agirre, Jon, et al.
(författare)
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The CCP4 suite: integrative software for macromolecular crystallography
- 2023
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Ingår i: Acta Crystallographica Section D. - : INT UNION CRYSTALLOGRAPHY. - 2059-7983. ; 79, s. 449-461
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Tidskriftsartikel (refereegranskat)abstract
- The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.
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- Berkelmans, G. F. N., et al.
(författare)
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Population median imputation was noninferior to complex approaches for imputing missing values in cardiovascular prediction models in clinical practice
- 2022
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Ingår i: Journal of Clinical Epidemiology. - : Elsevier BV. - 0895-4356. ; 145, s. 70-80
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To compare the validity and robustness of five methods for handling missing characteristics when using cardiovascular disease risk prediction models for individual patients in a real-world clinical setting.& nbsp;Study design and setting: The performance of the missing data methods was assessed using data from the Swedish National Diabetes Registry (n = 419,533) with external validation using the Scottish Care Information ? diabetes database (n = 226,953). Five methods for handling missing data were compared. Two methods using submodels for each combination of available data, two imputation methods: conditional imputation and median imputation, and one alternative modeling method, called the naive approach, based on hazard ratios and populations statistics of known risk factors only. The validity was compared using calibration plots and c-statistics.& nbsp;Results: C-statistics were similar across methods in both development and validation data sets, that is, 0.82 (95% CI 0.82-0.83) in the Swedish National Diabetes Registry and 0.74 (95% CI 0.74-0.75) in Scottish Care Information-diabetes database. Differences were only observed after random introduction of missing data in the most important predictor variable (i.e., age).& nbsp;Conclusion: Validity and robustness of median imputation was not dissimilar to more complex methods for handling missing values, provided that the most important predictor variables, such as age, are not missing. (C)& nbsp;2022 Elsevier Inc. All rights reserved.
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