Throttle alignment when the world shakes — never the numbers.
4.1 Telemetry Lanes (inputs to the gate)
Purpose. When contradictions spike, tools fail, or latency surges, apply a calm gate that scales alignment only so routing becomes conservative while magnitudes stay pristine (phi((m,a)) = m). The gate outputs g_t ∈ [0,1], and you use RSI_env := g_t * RSI (or a u-space variant).
Telemetry lanes (normalize each to [0,1]). Declare a few simple lanes (start with 3–5) and pin normalizations in the manifest.
F_t := clamp(frac_violations, 0, 1) # contradictions / policy hits
D_t := clamp( (1 - cos_sim) / max(1 - cos_ref, 1e-12), 0, 1 ) # semantic drift vs baseline (cos_ref~0.95)
L_t := clamp( (latency - p50) / max(p95 - p50, 1e-12), 0, 1 ) # latency pressure
E_t := clamp( error_count / max(calls,1), 0, 1 ) # tool/API errors
V_t := clamp( edit_distance / max(length,1), 0, 1 ) # response/token churn
Q_t := clamp( queue_depth / q95, 0, 1 ) # (optional) queue pressure
Instant gate (one-liner).
W := wF + wD + wL + wE + wV + wQ
g_inst := clamp( 1 - (wF*F_t + wD*D_t + wL*L_t + wE*E_t + wV*V_t + wQ*Q_t) / max(W, 1e-12), 0, 1 )
Smoothed gate (avoid jitter).
g_t := (1 - rho) * g_{t-1} + rho * g_inst # rho in (0,1], e.g., 0.20
g_t := clamp( max(g_min, g_t), 0, 1 ) # e.g., g_min = 0.00
Application (alignment-only).
RSI_env := g_t * RSI # or tanh(g_t * atanh(RSI)) if using u-scale mode
Worked numbers (calculator-fast).
F_t=0.20, D_t=0.10, L_t=0.30, E_t=0.15, V_t=0.20, equal weights → W=5
g_inst = 1 - (0.20+0.10+0.30+0.15+0.20)/5 = 0.81
RSI = 0.604368 → RSI_env = 0.81 * 0.604368 ≈ 0.489534 → band A0
Traditional vs SSM-AI (handling turbulence).
Goal: reduce waste and misroutes during instability.
• Traditional: fixed retries/timeouts; ignores semantic drift; cost spikes.
• SSM-AI: compute g_t from bounded telemetry; apply RSI_env := g_t * RSI (alignment-only). Below A0 back off; above A+ proceed. m never changes; all decisions are stamped.
Pseudocode (drop-in).
def calm_gate(F, D, L, E, V, Q=0.0, w=(1,1,1,1,1,0), rho=0.2, state=None, eps_g=1e-12, g_min=0.0):
wF,wD,wL,wE,wV,wQ = w
W = max(wF+wD+wL+wE+wV+wQ, eps_g)
g_inst = max(0.0, min(1.0, 1.0 - (wF*F + wD*D + wL*L + wE*E + wV*V + wQ*Q)/W))
g_prev = 1.0 if state is None else state["g"]
g = (1 - rho) * g_prev + rho * g_inst
g = max(g_min, min(1.0, g))
return {"g": g}
def apply_gate(RSI, gate_state, mode="mul"):
g = gate_state["g"]
if mode == "u_scale":
return tanh(g * atanh(RSI))
return g * RSI
Guardrails (declare once).
• Gate purity: acts on alignment outputs (RSI/bands) only; never on m.
• Visibility: log (F,D,L,E,V,Q), g_inst, g_t, mode, and RSI_env.
• Fallback: if telemetry is missing/corrupt, clamp to [0,1], set g_t := 1, flag, and continue.
• Stamping: append |g=...|RSI_env=...|gate_mode=...|lanes=... to your existing ASCII stamp for deterministic replay.
One-line takeaway. g_t ∈ [0,1] turns turbulence into a transparent, bounded brake on alignment—conservative when shaky, assertive when clear—while phi((m,a)) = m keeps numbers identical.
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