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| 2. |
- Patronis, N., et al.
(författare)
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Status report of the n_TOF facility after the 2nd CERN long shutdown period
- 2023
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Ingår i: EPJ TECHNIQUES AND INSTRUMENTATION. - : Springer Nature. - 2195-7045. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- During the second long shutdown period of the CERN accelerator complex (LS2, 2019-2021), several upgrade activities took place at the n_TOF facility. The most important have been the replacement of the spallation target with a next generation nitrogen-cooled lead target. Additionally, a new experimental area, at a very short distance from the target assembly (the NEAR Station) was established. In this paper, the core commissioning actions of the new installations are described. The improvement in the n_TOF infrastructure was accompanied by several detector development projects. All these upgrade actions are discussed, focusing mostly on the future perspectives of the n_TOF facility. Furthermore, some indicative current and future measurements are briefly reported.
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| 3. |
- Tagliente, G., et al.
(författare)
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The n_TOF facility at CERN
- 2024
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Ingår i: 16<sup>th</sup> Varenna Conference on Nuclear Reaction Mechanisms (NRM2023). - : EDP Sciences. - 9782759891245
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Konferensbidrag (refereegranskat)abstract
- The neutron Time-of-Flight facility (n_TOF) is an innovative facility operative since 2001 at CERN, with three experimental areas. In this paper the n_TOF facility will be described, together with the upgrade of the facility during the Long Shutdown 2 at CERN. The main features of the detectors used for capture fission cross section measurements will be presented with perspectives for the future measurements.
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| 5. |
- Aczel, Balazs, et al.
(författare)
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Consensus-based guidance for conducting and reporting multi-analyst studies
- 2021
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Ingår i: eLIFE. - : eLife Sciences Publications. - 2050-084X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.
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| 6. |
- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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