Individual skill
relsa-severity-assessment
Multivariate severity assessment and humane endpoint prediction 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 or when one will be reached, 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.
backend/cli/skills/biology/relsa-severity-assessment/SKILL.md
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- Last checked
- Nov 2, 2026
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- Nov 6, 2026
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- Apache-2.0
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# RELSA severity assessment and humane endpoint forecasting
## Overview
Severity assessment in animal research is legally mandatory and scientifically load-bearing:
it drives humane endpoint decisions, and poor welfare monitoring degrades reproducibility.
The usual practice evaluates each readout in isolation — weight loss here, a clinical score
there — which makes it hard to say how badly an individual animal is actually doing.
This skill implements two published procedures that address that:
- **RELSA** (Talbot et al., 2022) combines several outcome measures into one score per animal
per time point, expressed *relative to a reference set of known burden*. RELSA = 0 is
baseline; RELSA = 1 means the animal has reached the reference set's maximum deviation.