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An extensive experimental validation evaluates the query service and its alternative components.
The self-consistency validation evaluates the prediction accuracy merely on the benchmark data, while the leave-one-out validation and 4-, 6-, 8-, 10-fold cross-validations assess the performance and robustness on an independent data set.
The first validation evaluates NeuroRD simulations of diffusion of a single molecule species in a 10×11×1 µm rectangular cuboid subdivided into 110 subvolumes of size 1×1×1 µm.
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Event cross validation evaluated predictions during periods of high stream discharge.
Tier 2 assays, which are currently undergoing validation, evaluate dose responses between those interactions and chemical exposure.
Here, the 10-fold cross-validation evaluates the error from each variable into every single fold; it can be seen by Figures 15 and 16.
Based on the N feature subsets, N Random Forest predictors were constructed with 10-fold cross-validation evaluating its performance.
The second validation set evaluates NeuroRD simulations of reactions alone in the same morphology as the first validation using two reversible bimolecular reactions (A+B↔C and A+C↔D).
Primer design and validation were evaluated as described elsewhere [20].
Method validation was evaluated following the EU guidelines.
An experimental design was used during validation to evaluate method robustness.
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