Trust is structural when vendors publish red lights with the same energy as green lights. Below is the public safety cage for Zero Overshoot / GSRF Practical.
Red — do not use for these jobs
1. Delayed closed-loop command smoothing
MAD to delayed measured plant vs EMA (phase4-style delay packs): +59% worse at τ=3 min, +97% at 6 min, +106% at 10 min. The spring fights delayed truth. Use other tools for that path.
2. Fixed false-alarm event detection
At matched FA rate on synthetic excursions (residual mode): GSRF recall ~0.44 vs EMA ~0.83. Peak compression and higher normal residual raise the calibrated threshold. Pair a detector with GSRF—or use EMA residual for that task.
3. Minimum MAD tracking vs raw
Excellence hunt v2: 0 / 52 wins vs best EMA on tracking MAD. If your KPI is hug-the-raw, turn the spring down (or use EMA)—and accept losing the niche.
Green — designed for these jobs
- Mid-band oscillation kill (~+35% osc31; ~−70% sweet-band spectral power on locked packs)
- Peak compression toward defined normal (~38% mean; 49/52 wins)
- Adaptive x* when the plant’s normal truly moves
- Pre-model / pre-AI signal hygiene (calm first; detect separately)
Procurement wording
Prefer: “soft thermostat with published band and failure modes.” Avoid: “universal optimal filter” or “eliminates false alarms.” See the claim ladder on the Workbench page.
Sources: Evidence §4 · characterization v4 delay · probes v5 alarm · excellence hunt v2. /evidence#boundaries · /workbench