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relsa-severity-assessment

k-dense-ai/scie…t-skills

Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.

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安装命令

npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill relsa-severity-assessment

SKILL.md

RELSA severity assessment and exploratory score forecasting

Overview

This skill computes reference-relative multivariate scores and exploratory ARIMA forecasts. It targets the equations and printed example of RELSA 0.0.1.9000 (commit e68e8451e8719ccc3600179f55900cd7254ede9d, current upstream at review), plus the published foRcast methodology. The Python forecast helper is an independent nonseasonal approximation, not an exact R port.

RELSA is the RMS of directional deviations divided by each variable's reference maximum deviation. Zero means no measured worsening in those directions; it does not establish normal welfare. One is a reference scale unit, not a universal endpoint or an upper bound. Different variables may attain their reference extrema in different animals or at different times, so the reference cohort need not contain a score of exactly one.

Forecasts estimate a score at a specified time, not time-to-endpoint or probability of death. Keep the approved study's observation schedule and humane endpoint criteria separate from these exploratory outputs. See Boundaries.

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