research: Arc 1 — trend regime vs H1 breakout, campaign path, results page

Two std-vocabulary blueprints (bo_h1 donchian-style H1 breakout; bo_h1_trend
adds a post-latch EMA 12/48 regime gate). First real use of the campaign
path: process + campaign documents registered and run as executable intent
(screen 490d14df.., curves da886931.. with persisted taps).

Finding: the gate reshapes the R-distribution per instrument (GER40 flips
sign, EURUSD deteriorates); no deployable edge (best P(E[R]<=0)=0.08,
generalization floor negative, sign agreement 0/4, all gross of costs).

site/: build.py bakes a fully static index.html from the runs/ registry
(aura.css embedded verbatim, inline SVG, zero external requests);
adversarially verified — all baked figures re-derived from the registry.

docs/arc-1-breakout-trend.md

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+# Arc 1 — does a trend regime reshape the H1 breakout's R-distribution?
+
+**Date:** 2026-07-13
+**Engine:** aura @ `1ebb94c` (release build)
+**Results page:** `site/index.html` (build: `python3 site/build.py`)
+
+## Hypothesis
+
+Following the orthogonal confirm/refute research model: a lone signal is not
+expected to be profitable; the question is whether a *conditioner* B reshapes
+the R-distribution of a base signal A. Here A = an H1 donchian-style breakout
+(`blueprints/bo_h1.json`), B = an EMA(12)/EMA(48) trend regime that gates the
+held breakout state post-latch (`blueprints/bo_h1_trend.json`) — a held
+breakout is cut the moment the regime flips against it.
+
+## Method (campaign path, first real use)
+
+Everything ran as registered research documents — no ad-hoc verb flags:
+
+- `research/process-screen.json` — sweep (deflated argmax on sqn_normalized)
+  → 90/30-day rolling walk-forward refit → 1000-resample block-5 R-bootstrap
+  pooled over WF OOS trades → cross-instrument generalize (expectancy_r).
+- `research/campaign-arc1.json` (id `490d14df…`) — both variants × 4
+  instruments (GER40, US500, EURUSD, XAUUSD) × window 2018-01-01..2026-06-30,
+  channel axes {24,48,96}², risk Vol{3, 2.0}, seed 0. 8 cells, 76 s wall.
+- `research/campaign-arc1-curves.json` (id `da886931…`) — both variants at
+  default params, taps persisted (equity, exposure, r_equity) for the page.
+
+No cost block: all R figures are **gross** (net == gross).
+
+## Findings
+
+1. **The gate reshapes the R-distribution, instrument-dependently** (pooled
+   WF-OOS bootstrap, mean E[R] and P(E[R] ≤ 0)):
+   - GER40 **flips sign**: −0.151 (P≤0 = 0.90) → +0.139 (P≤0 = 0.18)
+   - US500 improves: +0.193 (0.10) → +0.205 (0.08)
+   - EURUSD deteriorates sharply: −0.150 (0.88) → −0.204 (0.99)
+   - XAUUSD roughly flat: +0.170 (0.14) → +0.124 (0.15)
+   This is the conditional effect the research model looks for: B is not a
+   uniform improvement, it is a per-instrument reshaping.
+2. **No deployable edge.** Best cell P(E[R] ≤ 0) ≈ 0.08 (US500 gated) — not
+   significant against 8 comparisons; generalization worst-case is deeply
+   negative for both variants with sign agreement 0/4; and all of it is
+   gross of costs.
+3. **Selection instability.** The full-window IS argmax picks asymmetric
+   channels (e.g. hi=96/lo=24) that wander across WF windows — the deflation
+   and param-stability records show the screen overfitting the grid, which
+   the WF/MC stages correctly deflate.
+
+## Verdict
+
+Honest null on deployability; positive on the machinery and on the research
+question's shape: the conditional framing (B reshapes A) is measurable with
+the recorded artifacts alone (MC quantile bands per cell). Arc 2 candidates:
+a costed rerun (constant + vol-slippage cost blocks) to see what survives
+gross-to-net, an orthogonal conditioner (time-of-day / volatility tercile),
+or the same pair on coarser bars (H4).
+
+## Engine friction
+
+None. The campaign path (process/campaign documents, three-tier validate,
+`aura campaign run` as executor, persist_taps traces) carried the whole arc
+on its first real use.