Sentence examples for poor predictive capability from inspiring English sources

However, these are shown to have poor predictive capability, even for the system from which they were derived.

The main reason for a poor predictive capability of the existing models is the absence of combustion contribution to the blast wave strength.

Whereas established liver function parameters such as transaminases and bilirubin showed poor predictive capabilities regarding prediction of a Catot /Caion ratio ≥2.5 in liver failure patients, a serum lactate level ≥3.4 mmol/l and a prothrombin time ≤26% where highly predictive for this endpoint.

Some results showed good agreement with the data, whereas other models had poor predictive capabilities.

In neurological research, it has been found that poor predictive capabilities are a basis for false attributions of actions, for example, for patients suffering from schizophrenia [38, 47, 48].

Most of the numerical benchmarks on combustion in large scale volumes for hydrogen safety, which were performed up until today have demonstrated, that current numerical codes and physical models experience poor predictive capabilities at the industrial scale, both due to under-resolution and deficiencies in combustion modeling.

Standard laboratory liver function parameters showed poor predictive capabilities regarding citrate accumulation in terms of an elevated Catot/Caion ratio ≥2.5.

Some of the conventional test results and empirical ratios generated out of it offer poorer predictive capability for slagging behaviour experienced in power plants.

Investigations show that the methods have limited predictive capability and most often poor transferability of fatigue test results for more complex geometries.

Model validation results reveal that inaccurate geological models yield poor drawdown predictions, but using more calibration data improves its predictive capability.

Furthermore, the third scenario handles a case in which a prepared action lacks satisfactory predictive effects (i.e. ω 24 = 0.2), and the fourth scenario addresses poor action prediction capability (i.e. ω 18 = 0.2); and so on (see Table 4).