The phrase "accuracy of the underlying" is correct and usable in written English.
It can be used when discussing the precision or correctness of foundational data, principles, or models in various contexts, such as research, statistics, or technology.
Example: "The accuracy of the underlying data is crucial for the validity of the research findings."
Alternatives: "precision of the base" or "correctness of the foundational".
The first is the accuracy of the underlying information.
However, the accuracy of the underlying force field underpins any estimation of binding free energies [20].
The efficient execution of construction projects depends highly on the accuracy of the underlying construction schedules.
We describe how this improvement depends on the population size and accuracy of the underlying theory.
The degree and precision of the IGRF has changed over time reflecting the increased accuracy of the underlying observing systems.
Evidence from earlier observations suggests that the accuracy of the underlying model directly influences the effectiveness of the anomaly detection method.
The scalar variable at cell faces is obtained by a symmetric central interpolation scheme, which is formally first-order accurate, or by further employing a high-order correction term which leads to formal second-order accuracy irrespective of the underlying grid.
It was found that literature data often misses important information and/or the required accuracy for resolution of the underlying mechanistic effects, especially when modelling reactor dependent variables.
The methodology employs implicit spectral element discretization of equations in each subdomain and explicit treatment of subdomain interfaces with spectrally-accurate spatial interpolation and high-order accurate temporal extrapolation, and requires few, if any, iterations, yet maintains the global accuracy and stability of the underlying flow solver.
Finally, we note that the value of any annotation-based similarity measure will naturally depend on the accuracy and comprehensiveness of the underlying annotation, i.e. if the annotations are not negligibility, inaccurate or subjective (33).
Most of the computer vision algorithms are developed for data lying in ℝ D. Applying these algorithms directly on the nonlinear manifold will yield poor accuracy as the underlying geometry of the manifold is ignored.
