Apply each family rule and its weight

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Each component first passes through its own family function and is then multiplied by its scalar weight. The family index chooses the update law, while the weight changes its contribution to the subsequent blending stage. A large or negative weight changes bounds and signs even when the unweighted family function has a bounded output.

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## 4.2 Family Application with Weights

```
Ψ'_i(t+1) = w_i · f_i(Ψ_i(t), inputs)
```

**Where**:
- `w_i` = weight for family i (tunable parameter)
- `f_i` = family function i

**Explanation**: Each family's contribution is scaled by its weight, allowing the system to emphasize different cognitive modes.

## 4.3 φ-Correction (Inertial Blending)

```
Ψ''_i(t+1) = 0.5 · Ψ'_i(t+1) + 0.5 · (Ψ_i(t-1) + (φ-1) · (Ψ_i(t) - Ψ_i(t-1)))
```

**Explanation**: This equation blends the new state with a momentum term based on the golden ratio. The (φ-1) ≈ 0.618 factor creates natural oscillation damping while preserving meaningful trends.

## 4.4 Stability Gating

```
γ = γ_min + (1 - γ_min) · clamp₀₁(stability)

Ψ'_i(t+1) = w_i · f_i(Ψ_i(t), inputs)

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