· Excellence hunt v2 · Multi-family

Peak compression 49/52 vs tracking MAD 0/52

Pre-declared excellence rules. Not “wins every metric.”

Most filter marketing shows one green column. Excellence hunt v2 ran balanced GSRF Practical against best EMA across multi-family datasets with official Phase5-style metrics. The interesting result is not a single win—it is the split.

Locked scoreboard

MetricWins / NMean advantage vs best EMAReading
Peak-dev compression 49 / 52 ~+37.8% Green — peaks pulled toward baseline
Tracking MAD vs raw 0 / 52 ~−412% (much worse) Red by design — spring costs tracking
Oscillation (synthetic actuator mocks) 30 / 30 ~+32.1% Green under predeclare rule

Family detail (selected)

Oscillation energy (lower better)

FamilyWins / NMean adv
phase6.2 oscillation mock3/3~+35.2%
phase5 mock (±noise)3/3~+21.5%
amplitude sweep A=1…1515/15~+38.0%
new regime (chirp / drift+osc / asym)9/9~+33.6%
VitalDB HR6/7~+14.1% (min −6.6%)
VitalDB SpO23/6−4.3% mean — not locked as win

Peak-dev compression

FamilyWinsMean peak-dev adv
All families49/52~+37.8%
Synthetic excursion3/3~+47.9%
VitalDB HR7/7~+30.6%
VitalDB SpO23/6mixed / negative mean

Why both numbers are true

Peak-dev measures how far filtered peaks sit from a series baseline (median). The spring to \(x^*\) pulls spikes home. Tracking MAD measures how far the filter sits from raw. The same spring refuses to hug raw. If your KPI is MAD-to-raw, you want EMA / Kalman / \(k_{\mathrm{return}}≈0\).

Explicit non-excellences (do not claim the opposite)

Verdict

Sell peak calm and mid-band kill. Publish the MAD loss in the same breath. That is how Zero Overshoot earns trust—same posture as publishing server-shutdown risk on comparison sites: show the failure mode that matters.

Sources: excellence_hunt_v2 · EXCELLENCE_FINDING_20260804.md · EXCELLENCE_AGGREGATE.json · /evidence · When GSRF lost

Questions people actually ask

What is 49/52 vs 0/52?

Excellence hunt scoreboard: GSRF won peak-deviation on about 49 of 52 datasets and tracking MAD on 0 of 52 vs best EMA — by design of k_return.

Should I optimize for both peaks and MAD?

They trade. The spring buys peaks/osc and costs MAD. Choose the KPI that matches the costly failure.

Where are the charts?

Evidence page and this note restating locked packs only.

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