Sentence examples for capacity for prediction from inspiring English sources

Across this region, the future strongly depends upon this incorporation and the amelioration of environmental change, the effects of these changes on human societies, and bridging the considerable gaps in research procedures, capacity for prediction, and in time- and space-scales that complicate the integration of human dynamics with environmental dynamics.

The study showed that the machine-learning software has a high capacity for prediction: it was between 80 to 86percentt accurate when identifying people who suffer from substance abuse, including tobacco, alcohol, and general drug addiction.

Phase 3 involves two components: fifthly, simulating the systems dynamics [ 60] of communities of practice and social networks and sixthly, testing the models' capacity for prediction [ 61].

The composition of predictors in Models 1 and 2 underline the importance of the patient's underlying health condition and regenerative capacity for prediction of ECMO outcome.

Plasma SPA on day 0 had a good capacity for prediction of mortality in ARDS patients: SPA on day 0 ≥38.8 ng/ml yielded a sensitivity of 65% and specificity of 80% (aUc 0.74; 95% Cl 0.577 to 0.866; P = 0.0026).

Hence, while the two germline variants show promising capacity for personalized prediction of unusual outcomes of the studied patient, their translation into clinical practice will strongly depend on the completion of more comprehensive genetic and functional studies in the future.

This cutoff will only reveal divergent regions of the MSA. 7. Regions: Nucleotides whose score is below the low cutoff boundary are reported as a putative SNP provided that each variation appears in at least two sequences (as a consequence, alignments of less than four sequences would lack the capacity for SNP prediction).

Characterization of performance limitations in the stochastic settting: entropy rate, rate-distortion function, channel capacity, Bayes envelope for prediction, denoising, and filtering.

A One Health approach rests on the assumption that the cross-sectoral integration of expertise, research methodologies and public health infrastructure will inevitably improve capacity for disease-risk prediction and effective intervention.

Given the convoluted history of the region and its demonstrated capacity for surprise, any predictions should be offered with caution.

Finally experiment results are used to calibrate existing analytical formulations for capacity prediction.