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    <responseDate>2026-10-13T04:07:03Z</responseDate>
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    <identifier>10.57760/sciencedb.32364</identifier>
    <datestamp>2026-04-13T10:14:27Z</datestamp>
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  <dc:date>2026-04-13</dc:date>
  <dc:title>Test dataset of Natural Spectra Quality Evaluator (NSQE)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.32364</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Natural Spectra Quality Evaluator，NSQE。 A natural spectral quality assessment method for evaluating the authenticity of simulated Raman spectra. Calculate the Mahalanobis distance of the baseline multivariate Gaussian model to evaluate the authenticity of the natural scene statistical features between the spectral dataset to be evaluated and the real spectrum. This method aims to objectively evaluate the authenticity of simulated datasets by quantifying the statistical distance between the measured spectrum and the true spectral statistical distribution. The data here is used to demonstrate the calculation process.&amp;nbsp;</dc:description>
  <dc:subject>Raman;  artificial neural network; simulated datasets</dc:subject>
  <dc:creator>huang wei xiang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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