Changed location for the logic on the Acknowledgements button
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2 changed files with 6 additions and 6 deletions
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@ -49,7 +49,11 @@ Although the user is able to calculate the infection probability of a stand-alon
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{{ text_blocks['Code Contributors'] }}
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<br>
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<h1 class="paragraph-title">Acknowledgements:</h1><br>
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{{ text_blocks['Acknowledgements'] }}
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<details>
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<summary>Click to expand</summary>
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<br>
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{{ text_blocks['Acknowledgements'] }}
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</details>
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<br>
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<a id="references_block" style="color:#2f4858"><h1 class="paragraph-title">References:</h1></a><br>
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{{ text_blocks['References'] }}
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@ -19,12 +19,8 @@
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<sup>4</sup>University of Manitoba<br>
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## Acknowledgements
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<details>
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<summary>Click to expand</summary>
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<br>
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We wish to thank CERN’s HSE Unit, Beams Department, Experimental Physics Department, Information Technology Department, Industry, Procurement and Knowledge Transfer Department and International Relations Sector for their support to the study. Thanks to Doris Forkel-Wirth, Benoit Delille, Walid Fadel, Olga Beltramello, Letizia Di Giulio, Evelyne Dho, Wayne Salter, Benoit Salvant and colleagues from the COVID working group for providing expert advice and extensively testing the model. Finally, we wish to thank Fabienne Landua and the design service for preparing the illustrations and Alessandro Raimondo and Manuela Cirilli from the Knowledge Transfer Group for their continuous support. Our compliments towards the work and research performed by world leading scientists in this domain: Dr. Julian Tang, Prof. Manuel Gameiro, Dr. Linsey Marr, Prof. Lidia Morawska, Prof. Yuguo Li, and others – their scientific contribution was indispensable for this project.
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</details>
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We wish to thank CERN’s HSE Unit, Beams Department, Experimental Physics Department, Information Technology Department, Industry, Procurement and Knowledge Transfer Department and International Relations Sector for their support to the study. Thanks to Doris Forkel-Wirth, Benoit Delille, Walid Fadel, Olga Beltramello, Letizia Di Giulio, Evelyne Dho, Wayne Salter, Benoit Salvant and colleagues from the COVID working group for providing expert advice and extensively testing the model. Finally, we wish to thank Fabienne Landua and the design service for preparing the illustrations and Alessandro Raimondo and Manuela Cirilli from the Knowledge Transfer Group for their continuous support. Our compliments towards the work and research performed by world leading scientists in this domain: Dr. Julian Tang, Prof. Manuel Gameiro, Dr. Linsey Marr, Prof. Lidia Morawska, Prof. Yuguo Li, and others – their scientific contribution was indispensable for this project.
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## References
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