Sentence examples for off the predicted from inspiring English sources

From the predictiveness curves, one could read off the predicted probability of an event for any corresponding true-positive fraction (sensitivity) or false-positive fraction (1 − specificity).

As underdogs go, there were literally none more under – they were still bottom of Fifa's rankings when the 2009 tsunami waterlogged their pitch – and this deluge of misfortune blows Mike Brett and Steve Jamison's buoying documentary off the predicted trajectory: for much of it, you can't see this lot scoring, never mind winning.

The predicted changes in body mass are flat, and although there are fluctuations between generations, by generation F14, the observed body masses are only +0.1 and −1.4% off the predicted body masses in Lines 1 and 2, respectively.

However, there seemed to be some exceptions among the bacteria analyzed, such as Mycoplasma gentalium (Table 1), where the minimum and maximum of the curve are significantly off the predicted balanced positions (202 degrees vs 180 degrees with a range of plus or minus 15 degrees in all other bacteria listed in Table 1).

The smooth fall off of the predicted flux with height above the bed is due to the consideration of separate particle elements which have different initial conditions at different points around the nose of the bubble.

The different cut-off points of the predicted probabilities resulted in different diagnostic efficiencies, indicating that the cases near the cut-off point require more attention.

However, it is also important that there are no anti-targets or off-targets of the predicted drugs in the host.

When the cut-off point of the predicted probabilities was decreased to 0.40, the sensitivities of the two models increased, whereas the specificities decreased.

When the cut-off point of the predicted probabilities was 0.40, the frequency of misdiagnosis of the two models was higher between 0.26-0.59 than for <0.26 and >0.59.

(iii) Receiver operator characteristic curves plot the true positive rate against the false positive rate for different cut-off values of the predicted score.

This indicates that when we use a mathematical model for predicting a clinical diagnosis, we have to pay close attention to the cases near the cut-off points of the predicted probabilities, as they are prone to misdiagnosis.