Model-assisted calibration integrates multiple probability surveys to boost regression efficiency while preserving design-based finite-population inference.
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A classifier-guided active sampling framework produces unbiased, lower-variance estimates of two-point correlations for rare target sources with far fewer human annotations than standard Monte Carlo sampling.
A multiscale colloidal deposition model with moving microscale boundaries is weakly solvable in the non-clogging regime and numerically shows clogging’s effect on dispersion and storage.
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Improving Efficiency of Regression Analyses by Integrating Data from Population-Representative Surveys: A Model-Assisted Calibration Approach
Model-assisted calibration integrates multiple probability surveys to boost regression efficiency while preserving design-based finite-population inference.
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Active Measurement of Two-Point Correlations
A classifier-guided active sampling framework produces unbiased, lower-variance estimates of two-point correlations for rare target sources with far fewer human annotations than standard Monte Carlo sampling.
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A Methodological Guide on Using Large Language Models for Reproducible Text Annotation in the Social Sciences and Humanities with Python and R
A multiscale colloidal deposition model with moving microscale boundaries is weakly solvable in the non-clogging regime and numerically shows clogging’s effect on dispersion and storage.