I understand your use of the word 'concordance' here but that word is also a statistical term that refers to measures of agreement among categorical variables.
I recommend using confidence interval estimates of the mean. The 'gold standard' is your null hypothesis H0: mean = 100) and therefore your alternative hypothesis is that the opposite (H1: mean not = 100). You compare the intervals to the gold standard and to each other using Analyze > Fit Y by X (Oneway platform). Here is your example in a data table laid out for Oneway:
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Here is the Oneway platform with a reference line for the gold standard and the results for ANOVA:
![capture.jpeg capture.jpeg](https://community.jmp.com/t5/image/serverpage/image-id/6115i457D86D89BB1E352/image-size/large?v=v2&px=999)
Now you compare the confidence interval for each sample. You can plot them in Graph Builder, too. Right-click on the Means for Oneway Anova table and select Make Into Data Table. It might look like this:
![capture.jpeg capture.jpeg](https://community.jmp.com/t5/image/serverpage/image-id/6116iB308DC8DF8C18F32/image-size/large?v=v2&px=999)