# Zero-shot prediction

Source: https://onco.cc/terms/zero-shot/  
OnCo record `zero-shot` (Term). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Zero-shot prediction applies a model to a task or class it was never trained on, with no task-specific labels at all.

## Summary

Zero-shot learning is the setting in which a model must predict classes it did not see in training (Wikipedia). For biology foundation models the zero-shot checks are whether embeddings cluster by tissue or subtype without labels (cluster purity, from cluster analysis) and whether a sequence model scores pathogenic variants above benign ones without being told which is which. A refuted zero-shot claim is still informative: it says the pretraining did not capture that biology.

## Fields

- Kind: Term
- Last checked: 2026-09-24
- Also known as: zero-shot; zero-shot prediction; zero-shot learning; zero-shot classification; zero-shot embedding quality; cluster purity
- Tags: cansim-terms

## Notes

- Listed in the CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme; CanSim page path /terms/zero-shot.

## Sources

- Wikipedia: https://en.wikipedia.org/wiki/Zero-shot_learning
- Wikipedia: cluster analysis: https://en.wikipedia.org/wiki/Cluster_analysis
- Wikipedia: https://en.wikipedia.org/wiki/Zero-shot_learning

## Connected records

- terms: [Autoregressive (next-token) modelling](https://onco.cc/terms/autoregressive-modelling/), [Cancer AI vocabulary (CanSim terms map)](https://onco.cc/terms/cancer-ai-vocabulary/), [Embedding (learned representation)](https://onco.cc/terms/embedding/), [Genomic and protein language models: Evo 2, Enformer, ESM](https://onco.cc/terms/genomic-and-protein-language-models/), [Transfer learning and the low-label regime](https://onco.cc/terms/transfer-learning/), [Variant effect prediction](https://onco.cc/terms/variant-effect-prediction/)

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JSON: https://onco.cc/api/v1/entities/zero-shot.json