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The goal of validation is not to identify a cut-off for statistical significance, but to compute a probability that the top-scoring peptide is the correct one.
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The major goal of internal validation is model selection.
The goal of the validation process is to determine how well a code can represent physical reality.
The goal of candidate validation is the improvement of detector robustness by the confirmation of correct detections and the rejection of false detections.
The ultimate goal of the validation of the computer codes for pebble bed HTR applications is to acquire and reinforce the capability of these general purpose computer codes for performing HTR core design and optimization studies.
The ultimate goal of the validation of the computer codes for PWR applications is to acquire and reinforce the capability of these general purpose computer codes to perform the core design and optimization study.
The goal of cross validation is to define a dataset to test the model in the training phase, in order to limit overfitting and give an insight on how the model will generalize to an independent dataset.
The goal of future validation efforts should not be restricted to identification of the highest quality approaches but should quantify the loss of data quality in choosing, for example, a truncated vs. complete live birth or pregnancy history, or a survey covering wide-ranging issues vs. a highly focused questionnaire.
The goal of cross-validation is to estimate the expected level of fit of a model to a data set that is independent of the data, which were used to train the model.
The goal of cross-validation is to define a dataset to test the model in the training phase.
The CHC nurses were not aware of the study goals of the validation study to prevent bias.
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