Sentence examples for model sensitivity for from inspiring English sources

Association between USLE predicted risk and observed erosion, estimated using mixed effects logistic regression to control for within-site variability, correctly classified only 38% of sites into three degradation classes and model sensitivity for delineating regions of severe degradation was only 28%.

Under that model, sensitivity for VIA (abnormal+) was 0.74 compared to 0.78 with conventional analyses.

Only 2.6% of pathogenic variants could be detected with threshold 0.9 when the full BrS model was used, while the sensitivity increased to 23% for the same threshold in the multivariate model (sensitivity comparison for other thresholds is summarised in Additional file 1: Figure S2 and Table S5).

Fig. 3 Results of the regression model sensitivity analysis for each study area.

The dynamic trend of the measures and model sensitivity analyses for Charlottetown facing increased frequency of severe storms, storm surges, and sea-level rise provide impetus for enhanced community strategic planning for the changing coastal environment.

To avoid reporting spurious results, our simulations included careful tuning of hyperparameters to minimize model sensitivity, steps for assessing convergence of the algorithm and applied different normalization and preprocessing methods.

Traditionally, model sensitivity is evaluated for model parameters.

A conscious effort can be made to collect data evenly and models can be redesigned to make sure that model sensitivity is similar for various parameters.

A Bayesian approach was used for model sensitivity and uncertainty analysis.

To account for model sensitivity to individual parameters, Latin hypercube sampling (LHS) was used to take many representative samples of the model dynamics across the parameter space.

The pipeline contains an implicit analysis of the model sensitivity and the parameter identifiability for model reduction.