Sentence examples for a poor prediction of from inspiring English sources

The Smagorinsky SGS closure model was selected in preference of traditional estimation models, however all the models used gave a poor prediction of energy dissipation for the flow conditions studied.

It was also shown that for certain values of the parameters, especially at high velocities, the Galerkin method using stationary string eigenfunctions can give a poor prediction of the dynamic response.

For the largest incidence investigated, Amiet's response function does not predict the total surface pressure difference as accurately as for zero or small incidence at the vortex shedding frequency, resulting in a poor prediction of the directivity and amplitude of the acoustic pressure.

The mapping of polynomial parameters was validated using an external SOC profile dataset and showed a poor prediction of the surface content but a good prediction of the depth distribution once the surface SOC content is known (RMSE = 0.15 0.25%C).

V ˙ O2max in itself is known to be a poor prediction of run performance.

However, our study shows that it has a poor prediction of adverse maternal and perinatal outcomes.

Since efficacy in one or more preclinical animal tumor models generally provides the rationale in support of a new anti-neoplastic drug's probable benefit in humans, is the primary modifiable cause of attrition of new drugs a consequence of poor prediction of human activity/potency from animal models?

As such, family history alone is a blunt tool in a population setting and overall has poor prediction of which women will develop BC as the majority of women even with early-onset BC do not have a family history of the disease [ 21].

The most likely explanation, however, is that poor predictive power is related to poor prediction of the single items themselves at this early age.

However, in sera, syndecan-1 showed poor prediction of a malignant disease (odds ratio 1.31, 95% CI 0.26 to 6.65; AUC 0.51, 95% CI 0.43 to 0.59); Nagelkerke's r < 0.01; goodness of fit = 0.54; discrimination slope < 0.01).

Rising incidence, increased risk among migrants to higher risk regions, and poor prediction of individual risk have prompted a search for additional modifiable factors.