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The limitations, accuracy and precision of these methods are discussed.
However, the application ranges and forecasting precision of these methods vary considerably.
Analysis demonstrates that the efficiency and precision of these methods can be improved clearly with the proposed suggestions.
As evidence for the precision of these methods, some of the results (e.g. the BACE1 set) show single-digit compound overlaps that have been verified by manual inspection.
This greatly damages the precision of these methods.
The problem for any practitioner, however, is to assess the precision of these methods.
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Based on the scientific reports, the precision all of these methods were better than the empirical formulas.
To compare the estimator bias and precision of these four methods, we calculated the root mean square error (RMSE) from 1000 estimates using each of these four methods on 1000 simulated pseudo-observed data sets with parameters randomly drawn from the priors.
The true variants of the samples served as the reference call set during the comparisons, i.e. we measured sensitivity and precision of the methods with respect to these variants.
Precision of the methods was evaluated by 15 double wear measurements.
Since no migration of the implant in relation to the sawbone occurred, this difference represents the precision of the methods.
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