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A Bayesian framework to update scaling factors for radioactive waste characterization

Biagio Zaffora 1 Séverine Demeyer 2 Matteo Magistris 1 Elvezio Ronchetti 3 Gilbert Saporta 4 Chris Theis 1 
1 CERN [Genève]
2 LNE - Laboratoire National de Métrologie et d'Essais [Trappes]
3 UNIGE - Université de Genève = University of Geneva
4 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
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Journal articles
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https://hal-cnam.archives-ouvertes.fr/hal-02491880
Contributor : Gilbert Saporta Connect in order to contact the contributor
Submitted on : Wednesday, February 26, 2020 - 2:31:26 PM
Last modification on : Friday, September 30, 2022 - 11:26:51 AM

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CNAM | LNE | UNIV-HESAM | CEDRIC-CNAM

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Biagio Zaffora, Séverine Demeyer, Matteo Magistris, Elvezio Ronchetti, Gilbert Saporta, et al.. A Bayesian framework to update scaling factors for radioactive waste characterization. Applied Radiation and Isotopes, Elsevier, 2020, pp.109092. ⟨10.1016/j.apradiso.2020.109092⟩. ⟨hal-02491880⟩

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