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README.md

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+# YarrowLab
+
+Post-training research on **bounded deviation from a statistical prior** for
+event forecasting.
+
+Instead of asking a model to output a probability directly, we train it to
+output `Δ` — a bounded deviation from a prior `p₀` computed upstream from
+reference-class statistics — plus an attribution category for *why* the
+prior might be wrong, and an evidence span supporting that attribution.
+The final probability `p = σ(logit(p₀) + Δ)` is composed in code; the model
+never sees or touches market prices.
+
+## Repositories
+
+- [`yarrow-delta-sft-v1-smoke`](https://huggingface.co/YarrowLab/yarrow-delta-sft-v1-smoke) —
+  a pipeline-validation checkpoint (LoRA over a randomly initialized tiny
+  model). Confirms the SFT loop runs end to end; not a trained model.
+
+More will be added here as real training runs land.