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The problem may be derived from a number of reasons.
We would like to ask you for some more information:
1. Have you scanned new samples in different temperatures? (specifically different temperatures than measured when collecting the database)
2. Have you used actual different samples or scanned multiple scans for identical samples and referred them as new samples?
3. Did you use the solid sample holder?
A high correlation on a low number of samples can originate from over-fitting as well (in over-fitting, a statistical model describes random error or noise instead of the underlying relationship).
Therefore, even if the classification model seems successful, it is not robust.
May I ask which samples did you scan? Can you please add a photo of the samples in the data collection?