An agentic AI measurement tool for deep research over local corpora of PDF and Markdown documents. Given a research question, it orchestrates a programmatic AI pipeline to exhaustively evaluate, synthesize, and verify information from your documents, producing a Markdown report with inline footnote citations -- then automatically measures the quality of every citation using LM-judge measurement probes.

"polysr: Symbolic Regression applied to Polymeric Use Cases" is a GitHub repository that demonstrates the utility of symbolic regression for understanding polymer data. Specifically, three distinct use cases are considered. The Robust to Noise use case demonstrates the robustness of symbolic regression to noise. Both the case where noise is added to the predicted quantity and the case where noise is added to one of the features are considered. Specifically, synthetic data is generated from the Flory Huggins spinodal equation for the tests.

Provides data for veterans of the United States on Vietnam-theater and Persian Gulf-theater status, service-connected income, effect of a service-connected disability on current labor force participation and participation in veterans' programs.

Provides data for veterans of the United States on Vietnam-theater and Persian Gulf-theater status, service-connected income, effect of a service-connected disability on current labor force participation and participation in veterans' programs.

The Community Resilience Estimates for Puerto Rico track how socially vulnerable every neighborhood in Puerto Rico is to the impacts of a disaster. The Community Resilience Estimates use Puerto Rico Community Survey microdata and Population Estimates Program data to measure the ability of individuals and households to absorb the external stresses of the impacts of a disaster.

The Community Resilience Estimates for Puerto Rico track how socially vulnerable every neighborhood in Puerto Rico is to the impacts of a disaster. The Community Resilience Estimates use Puerto Rico Community Survey microdata and Population Estimates Program data to measure the ability of individuals and households to absorb the external stresses of the impacts of a disaster.

Theoretical calculation, modeling and experimental measurement data for the paper "Integrated optical isolators for broadband multi-laser operation" accepted for publication in Nature Photonics (2026)

Repository for NIST-EPA Legionella study Python tools. Includes scripts for aerosol particle size distribution analysis, emission-rate calculations, data cleaning, visualization, and statistical modeling of shower-generated aerosols under varying temperature, humidity, and exhaust-fan conditions.

Python-based automation system for the NIST Building 423 Manufacturing House IAQ test facility. Provides incremental backups of instrumentation data, weather station logs, and thermostat telemetry to mission network storage with detailed error logging, retry logic, and support for scheduled execution.

With this tool, users can rapidly calculate binary classifier metrics like Matthew's Correlation Coefficient, F-Scores, and Average Precision Scores from scalar and binary predictions. It is primarily used to calculate threshold sensitivity studies, and has several routines to significantly speed up metric calculation (or approximation) when aggregate measures of performance over all thresholds are needed.