BOLT
with substantial index movement , these animals will be the exception to the rule .
9 . How does BOLT improve our calculation of accuracy ?
“ True ” accuracy can be thought of as the gold standard of accuracy . It is statistically unbiased , and therefore the ultimate measure of accuracy . True accuracy is the accuracy resulting from direct calculation . Unfortunately , even with the massively powerful computing capacity now in existence , the direct calculation of accuracy is not possible on datasets the size of ours . Because we cannot calculate accuracy directly , other approaches to accuracy calculation have been developed .
In our Cornell evaluation platform , and all others in existence other than BOLT , the calculation of the accuracy associated with each EPD is achieved through “ approximation ” methods . It has long been known these methods are a very crude approach to the calculation of accuracy — tending to overestimate accuracy .
Another approach to the calculation of accuracy is via “ sampling ” methodology . Sampling is shown to be a more accurate predictor of accuracy . In fact , the results of this method were reported to be virtually identical to
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true accuracy . Unfortunately , due to its computationally intense nature , sampling has long been thought an infeasible approach to the calculation of accuracy on large databases .
BOLT , however , has changed the landscape in this area . By employing unique computing strategies that leverage both software and hardware efficiencies , BOLT performs what was previously unthinkable — utilizing a sampling methodology to calculate what is essentially true accuracy .
Because BOLT can calculate true accuracy , we can put more confidence in our accuracy metrics . Put another way , unlike with approximation , we can count on the predicted movements associated with possible change holding true over time . This was not the case with our Cornell system nor any other system in existence .
10 . Why do the carcass EPDs generally have an increase in accuracy with BOLT while this is not a case for other traits ?
You will notice that while the Multi-breed Genetic Evaluation powered by BOLT will generally produce lower accuracies than the Cornell system for growth and calving ease traits , the opposite is true for carcass traits .
One reason behind the differing accuracy outcomes is several years ago the evaluation team developed a way to temper inflated accuracies in the Cornell carcass evaluation . Unfortunately , this was not possible for growth traits .
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Another reason is that the Cornell system only used the carcass and its corresponding ultrasound trait ( e . g ., marbling score and IMF ) to predict carcass EPDs , while records on several additional correlated traits are leveraged with the BOLT system .
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