Retitle: lead with method + separate working frozen heads from collapsed CD4-native negative
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README.md
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- state-model
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# RefineRx —
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RefineRx
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embedding (ST-SE) backbones.
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**Paper:** *When Does a Perturbation Model Know Enough? Learned Halting as a
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Biological Model Readout* (Yash Raj).
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- state-model
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---
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# RefineRx — adaptive-depth halting as a per-perturbation signature on STATE
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RefineRx adds a **learned, per-perturbation adaptive-depth halting** mechanism to
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the ARC **STATE** perturbation-response architecture, and asks whether the
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resulting halting depth E[N] is a reproducible, effect-size-independent signature.
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This repository ships both the **positive** and the **negative** result of that
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question:
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- **✅ Positive (the working artifacts): four `oracle-ACT` halt heads** on **frozen**
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Replogle cell-line STATE-embedding (ST-SE) backbones. Read off a fixed,
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gradually-refining backbone, these recover a usable per-perturbation depth
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signature (reproducible within-line, effect-independent, non-redundant with
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network topology).
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- **⚠️ Negative (documented, for the record): CD4-native fused-halting checkpoints**
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trained from scratch on CD4+ T-cell **pseudobulk**. The response head fits, but
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the halting depth **collapses to a constant** on this pseudobulk substrate — see
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the key result below. These checkpoints are shipped as the reproducible negative,
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not as a recommended depth model.
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> **Naming note.** "CD4-native" refers only to the from-scratch pseudobulk
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> checkpoints in `checkpoints/`; it is the *collapsed* model. The usable
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> depth signal in this repo comes from the frozen-backbone halt heads in
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> `halt_heads/`.
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**Paper:** *When Does a Perturbation Model Know Enough? Learned Halting as a
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Biological Model Readout* (Yash Raj).
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