The passive gamma spectroscopy (PGS) is a useful technique to extract information on spent nuclear fuels without any destructive actions. This method requires a correlation between number densities (NDs) of target nuclides, and it is generally estimated by numerical simulation. Therefore, the prediction accuracy of these nuclide generations is one of the key issues in PGS. Nuclear data used in nuclear fuel depletion calculations is one of the dominant uncertainty sources, so we quantify nuclear data-induced uncertainties of NDs of six fission product nuclides, which are important in PGS: Ce-144, Cs-134, −137, Ru-106, Sb-125, and Eu-154. Generation mechanisms of these nuclides are quantitatively investigated through sensitivities of these NDs to nuclear data. With the sensitivities and covariance data of nuclear data, uncertainties of NDs of these nuclides are quantified. The uncertainties of Ce-144, Cs-137, and Ru-106 are less than 2%, and that of Sb-125 is around 6%. In these uncertainties, fission yield uncertainties are dominant. On the Cs-134 and Eu-154 generations, total uncertainties are around 5% and uncertainties of (n,$\gamma$) cross-sections are dominant.

被动伽马能谱（PGS）是一种有用的技术，可在不进行任何破坏性操作的情况下提取乏核燃料信息。该方法需要目标核素的数密度（NDs）之间的相关性，并且通常通过数值模拟来估计。因此，这些核素世代的预测准确性是PGS中的关键问题之一。核燃料耗竭计算中使用的核数据是主要的不确定性来源之一，因此我们对六种裂变产物核素的ND的核数据引起的不确定性进行量化，这在PGS中很重要：Ce-144，Cs-134，-137，Ru -106，Sb-125和Eu-154。这些核素对核数据的敏感性通过定量研究了这些核素的生成机理。利用核数据的敏感性和协方差数据，对这些核素的ND的不确定性进行了量化。Ce-144，Cs-137和Ru-106的不确定度小于2％，Sb-125的不确定度约为6％。在这些不确定性中，裂变产率的不确定性占主导。在Cs-134和Eu-154世代中，总不确定度约为5％，而（n，$\gamma$）的横截面占主导地位。