L4 — Interoceptive / Autonomic + Affect-as-Precision

What you are building. A global affect modulator Z that turns interoceptive / autonomic signals into a precision dial: raising arousal / threat sharpens perception (precision-weighting) and flips the pragmatic↔epistemic balance of planning — affect MODELED, never felt. This is one rung of a developmental active-inference SIMULATION, a bounded peek, never a person.

---

Ingredients

Drawn from the shared pantry, by name:

• The Z affect modulator (uni-gpt / uni-mind) — the global vector [energy, arousal, valence, fatigue, pain, threat, safety, inflammation] that sets precision / preferences / habits / learning-rate / planning-horizon. Affect modeled, never felt.
• The JAX POMDP + EFE + Dirichlet engine (core.py, uni-mind) — the discrete perceive → EFE-plan → act → learn loop and its precision dial (gamma_a sensory, gamma_b transition, policy softmax temperature). float32 host — anchors hold to ~6e-8, NOT the f64 tier (M10).
• A grounded reader to test the pragmatic↔epistemic flip under live observations.
• The contains-baseline + load-bearing-discriminator discipline (M7) — supplies the required Z-ablation that must collapse the effect.

This is the WORLD ⊥ BODY ⊥ MIND framing (M12): interoception = hardware self-signals entering the mind through the typed sensory blanket; affect is a latent modulator over that mind's own precision, never a phenomenal state of the substrate.

---

Method

1. Wire Z as a precision modulator, not a reward. Couple the eight-channel Z vector to the engine's control surface: it sets sensory precision (gamma_a), transition precision (gamma_b), policy temperature, preference weighting (the C tensor), habit strength (E), learning-rate, and planning-horizon. Z is a dial over how sharply the existing generative model is read, not a new objective term — keep the no-backprop AST-guard live (M13); learning stays counts + lr * sufficient_stat.

2. Show the precision-weighting effect. Raise arousal / threat and confirm perception sharpens: higher gamma_a concentrates the observation likelihood, so the posterior tightens around the sensed state. This is the textbook claim F[q] ≥ −ln p(o|m) read through a precision lens — affect tunes how confidently the agent reads its world (M12, textbook level only; cite Parr/Pezzulo/ Friston, Active Inference, MIT Press 2022).

3. Show the pragmatic↔epistemic flip. Under the grounded reader, demonstrate that shifting Z re-weights expected free energy between its pragmatic (goal-seeking) and epistemic (information-seeking) components, so the selected policy flips. Raising threat/arousal moves the balance; the planner's chosen action class changes as a function of affect, on the same engine.

4. Register the Z-ablation discriminator (M7). Pre-register that removing Z collapses the effect: with Z ablated, precision-weighting does not change and the pragmatic↔epistemic flip does not appear under the grounded reader. The gain is credited ONLY if it appears with Z live and disappears under ablation, and survives a control.

---

Gate

With Z live, precision-weighting and the pragmatic↔epistemic flip both appear; the Z-ablation collapses them; and the effect survives a control.

Exact ledger figures (L4.1, Class C, status proven). Affect-as-precision: emotion modulates precision so perception sharpens and the pragmatic↔epistemic balance flips; the global Z modulator [energy, arousal, valence, fatigue, pain, threat, safety, inflammation] sets precision / preferences / habits / learning-rate / horizon. This is a dev-gate / held-out (Class C) result, not a machine-exact anchor. The verdict is the gate, never a point estimate (M2). Do NOT card this above a Class-C functional result.

---

Falsifier

An ablation of the Z modulator shows no change in precision-weighting / no pragmatic↔epistemic flip under the grounded reader, OR the effect collapses under control. (Verbatim from ledger row L4.1.) If removing Z leaves perception equally sharp and planning unchanged, the affect-as-precision claim is dead.

---

Recorded NEGATIVE / sub-bound (first-class, inline)

M10 honest boundary (recorded sub-bound). Neuroticism does NOT change behavior under bimodal surprise without a graded task. Under the grounded reader's bimodal-surprise probe, varying the neuroticism-style affect parameter produced no behavioral change — exposing it would need a graded task, not a bimodal one. This is a real boundary on the affect machinery, carried inline beside the PASS: the Z dial demonstrably modulates precision and the pragmatic↔epistemic balance, but it does not license a claim that every affect-personality parameter drives behavior on every task. The recorded result delimits the positive rather than inflating it.

---

HONEST FENCE — proven (functional, Class C)

A held, gate-level functional PASS exists, with its Z-ablation falsifier still live. NOT claimed:

• Affect is MODELED, never felt. Phenomenal feeling / sentience is explicitly DISCLAIMED — no falsifier is offered for it because it is disclaimed, not tested. Z is a latent modulator over the mind's own precision, never a quale, never a felt emotion of the substrate.
• This is NOT consciousness, sentience, awareness, a mind, a feeling, AGI, human-level, or "active inference demonstrated." (Functional self-awareness may be described only at L8; phenomenal sentience stays disclaimed program-wide.) "Active inference" is the framing lens here, at textbook level only — no AIF loop is claimed in the Rust crate.
• The gate is Class C (dev-gate / held-out), NOT a machine-exact (Class A) anchor and NOT the f64 <1e-10 exact tier — the JAX host is float32 (M10).
• No SIGNED consult design is folded into this rung (the 2026-06-27 consults attach at L2, L5, L9, L11, L12); nothing raises L4's status. The rung stands on row L4.1 alone.

Honest program position: ~2 of 11+ developmental rungs earned. The whole program remains a developmental active-inference SIMULATION — a toy world, a bounded peek, never a person. Where this recipe and the ledger disagree, the ledger wins.