# Bishal

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [Bishal Shrestha](https://cerebralvalley.ai/u/OfficialBishal)
- **GitHub:** https://github.com/OfficialBishal/PertEMA
- **Demo video:** https://youtu.be/Id5JlmExXWM
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/201

PertEMA is a post-hoc, model-agnostic reliability layer for single-cell perturbation-effect predictors. Deep models that predict how a CRISPR perturbation reshapes gene expression are used to nominate experimental targets, but on unseen perturbations they rarely beat a trivial mean baseline. Instead of building a better predictor, I ask which individual predictions can be trusted: a gradient-boosted-tree meta-model estimates each prediction's error from prediction-time features only, with isotonic calibration and split-conformal intervals.

On the genome-scale Gladstone CD4 T cell Perturb-seq screen, the reliability score ranks realized error above the effect-magnitude and training-similarity heuristics, calibrates to near-nominal coverage, and builds a validation shortlist that is measurably more reproducible than ranking by effect size. I also characterized where reliability cannot help: per-instance model routing is infeasible, because candidate predictors co-fail on the same hard, noise-dominated perturbations. I quantified this with a measured noise ceiling and a break-even condition, and I pre-registered a routing test on an independent screen that failed exactly as predicted.

Why it matters: it gives perturbation-prediction users a calibrated, honest abstention signal on real primary data, plus a transferable, reproducible finding about the limits of per-instance model selection, shipped as a self-hostable tool and an open reliability benchmark.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/201. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt