feat(risk-monitor): measure the rule that fires, and give fundamentals their own channel

The Warning study measured a fitted percentile crossing that nothing consumes.
What reaches Telegram is a quadrant change: fixed 50/40 dividers, hysteresis,
two-session confirmation, 3-day cooldown. Those thresholds are constants, not
fits, so there is no training set to protect and all 11 detected corrections are
evaluable instead of the 4 that fell in a holdout.

Replaying it: 1/10 corrections, 0.9 false alarms/year. Random alarms at the same
firing rate match or beat that in 65% of draws. The panel now carries ablations
(does the quadrant machinery earn its place?), external baselines (does the score
earn its complexity?), and that null, because a bare "2 of 4" was unreadable in
either direction. Nothing in the alert path was retuned on the strength of it.

Fundamentals become a third channel rather than a term in either score. v3 cut
them arguing 12+8 of 100 points "could not change any published conclusion" --
true only when every technical sensor reads zero; weighted they moved the bar for
the 40 divider from 40 to 25. But no fusion weight is measurable either: with ~10
events and no fundamental history, any weight is a policy preference presented as
a measurement. So the read is a categorical state (supportive/neutral/adverse/
unknown) with an evidence grade, derived by fixed rules from stored facts, read
by confluence. The LLM extracts and explains; it does not score.

Absence stays absence throughout. `unknown` is unreachable by averaging, a stale
or empty observation may display but never confirm, extraction failures map to
`unknown` rather than `mixed`, and the study rows are coverage-matched and marked
not-measurable until enough corrections are covered -- otherwise a fortnight of
observations renders as 0/10 and reads as a failed test.

Observations become a real time series (migration 033); they lived in a single
overwritten settings slot, so no history existed to replay. Pre-rename snapshots
are adapted rather than discarded. METHODOLOGY stays v4 -- no score changed --
so no reseed; STUDY_SCHEMA moves to 3 and discards the cached report.

Post-deploy: re-run Event Study from Admin -> Jobs. The panel reads "not run yet"
until then.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

docs/research/regime-monitor-v4.md

@@ -39,6 +39,162 @@ session, the calendar anchors, 100% coverage on every row, and a row-wise
 `state_v4 <= state_v3` invariant. Reading a calibration result out of a run whose
 pipeline did not validate is meant to be structurally impossible.
 
+## The fundamental channel (2026-08-12)
+
+The monitor has **three channels**, not two scores with a decoration:
+
+- **State** — current observable technical stress (price, breadth, credit, volatility).
+- **Warning** — observable deterioration that may precede stress (breadth
+  divergence, relative strength, credit impulse).
+- **Fundamental context** — a categorical state (`supportive` / `neutral` /
+  `adverse` / `unknown`) with an `evidence_quality` grade.
+
+The third is **never a term in the other two**. They are read together by
+confluence:
+
+| Warning | Fundamentals | Reading |
+|---|---|---|
+| Calm | Supportive/neutral | Normal |
+| Elevated | Supportive/neutral | Technical warning, not fundamentally confirmed |
+| Calm | Adverse | Fundamental concern; tape has not confirmed |
+| Elevated | Adverse | Confluence — highest attention |
+
+`METHODOLOGY` stays **v4**: no score changed, so partitioning the history API and
+discarding the event study cache would be churn. `STUDY_SCHEMA` moved to 3
+instead, and is now the only thing that discards a stale report.
+
+### Why the read is a channel and not a weight
+
+Two things are true at once, and only this shape honours both.
+
+**v3's reason for removing fundamentals from the score was wrong.** Not stale —
+wrong. v3 argued that F1 (capex) and F3 (good-news-stock-down), carrying 12 + 8
+of 100 Warning points, "could not change any published conclusion" because pegged
+they produced a Warning of exactly 20.0, below the alarm threshold. That
+arithmetic holds only when *every* technical sensor reads exactly zero, which is
+the one case that never matters. Warning is a weighted average, so the sensors
+add:
+
+| technical Warning | without fundamentals | with them pegged | delta |
+|---|---|---|---|
+| 0 | 0.0 | 20.0 | +20.0 |
+| 20 | 20.0 | 36.0 | +16.0 |
+| 25 | 25.0 | **40.0** | +15.0 |
+| 35 | 35.0 | **48.0** | +13.0 |
+| 50 | 50.0 | 60.0 | +10.0 |
+| 80 | 80.0 | 84.0 | +4.0 |
+
+Pegged fundamentals lowered the technical Warning needed to reach the 40 quadrant
+divider from 40 to 25. That is a 15-point shift in where the alert fires, which
+is emphatically a changed conclusion. The v3 section below is kept as written,
+with this correction attached, because its reasoning is cited elsewhere in this
+file and a silent overwrite would hide that the error was ever made.
+
+**But no weight is measurable either.** A weighted modifier was built and
+reverted: 0–25 points added onto the technical Warning, sized so a maxed-out read
+carried a calm tape over the 40 divider on its own. Nothing could justify the 25.
+With ~10 correction events and essentially no fundamental history, any fusion
+weight is a policy preference presented as a measurement — and the debate it
+invites ("does the read deserve 10%, 20%, 30%?") has no evidence that can settle
+it. Adding a slow categorical judgement to a fast continuous score also
+manufactures precision by summing unlike things, and it forces a missing
+observation to silently redistribute its weight onto the technical sensors, which
+is the opposite of leaving it unknown.
+
+So: the read gets a channel, not a coefficient. Both facts survive — the v3
+removal was badly argued *and* no weight is defensible — because "report it
+separately" is the only design that neither buries the observation nor invents a
+number for it.
+
+### Derivation
+
+Deterministic, from the stored categorical facts. The LLM is an **extraction and
+explanation layer**: it finds the capex guidance, classifies it, and cites it.
+Fixed rules turn those facts into a state, so the same observation always yields
+the same category.
+
+`capex_signal`: any `cutting` → adverse; else any `holding` → neutral; else all
+known `raising` → supportive; nothing known → unknown.
+`reaction_signal`: `yes` → adverse, `mixed` → neutral, `no` → supportive,
+`unknown` → unknown.
+
+`mixed` and `unknown` are different reaction states and were merged until
+2026-08-13. A failed LLM parse fell back to `mixed`, so an extraction error
+became *neutral evidence* — an observation of normality manufactured out of a
+bug. `mixed` now means an observed mixed reaction; anything unreadable, missing
+or unattempted is `unknown` and contributes nothing.
+
+Combined by precedence, never by averaging: **any adverse read carries**; both
+unknown → unknown; every observed signal supportive → supportive; otherwise
+neutral.
+
+`unknown` is deliberately unreachable by combination. Averaging would let two
+`cutting` reads and two `unknown` ones land on "neutral", presenting missing
+evidence as evidence of normality — the same conflation `current_observation`
+already refuses between "no observation" and "an observation of zero". Two cuts
+and two unknowns read **adverse with `evidence_quality: partial`**.
+
+`evidence_quality` is ordered by what an operator needs first: `unavailable`
+(nothing collected) → `stale` (past `fundamental_staleness_days`) → `manual`
+(hand override) → `complete` / `partial`.
+
+### Presentation and alerts
+
+The Path view colours each dot by the fundamental state recorded that day; the
+axes are untouched, because context is confluence information rather than a
+position on either axis. The card leads with the state and evidence grade.
+
+Alerts stay **separate**, off one toggle:
+
+- quadrant change — the market axes moved (existing);
+- `regime_fundamental` — the context changed, e.g. neutral → adverse;
+- `regime_confluence` — Warning elevated *and* fundamentals adverse.
+
+`unknown` never alerts: an absence of evidence is not a change in the evidence,
+and alerting on it would train the reader to ignore the channel. Both new
+triggers seed silently on first run, as the quadrant alert does.
+
+### The observation is now a real time series
+
+`regime_fundamental_observations` (migration 033), one row per `effective_date`,
+upserted. Before this it lived in a single `SystemSetting` slot that every
+refresh overwrote, so no history existed at all — which made the read impossible
+to replay, impossible to backtest, and meant a rebuild recorded every historical
+session as if nothing had been observed. `update_regime_monitor` carries the
+pre-existing single-slot observation into the series on its next run.
+
+### What this does not establish
+
+The table starts empty and fills one observation at a time, so the fundamental
+rows are **untested, not failed**. Two things enforce that rather than one:
+
+- they are **coverage-matched** — scored only on sessions where the channel had
+  usable context and on corrections whose warning horizon fell inside it, with a
+  market-only comparator over the identical window so any difference between them
+  is the channel and not the window;
+- `measurable` stays false until `MIN_EVENTS_FOR_CONFIDENCE` corrections are
+  covered, and the panel prints "insufficient exposure" rather than a ratio.
+
+Without the first, one day of coverage would render as 0/10 — recreating, one
+observation later, exactly the tested-versus-unavailable confusion the flag was
+added to prevent. The market rows are unchanged, and the 1/10 shipped-rule figure
+remains a verdict on the technical sensors and the alert machinery alone.
+
+The rationale for expecting the read to matter is the operator's: hyperscaler
+capex is the demand side of the entire AI trade, and good earnings being sold is
+a classic late-cycle tell. Both are plausible. Neither is measured here, and this
+file's convention is that published numbers are reproducible.
+
+**The path forward is accumulation, then a test — in that order.** Once enough
+point-in-time observations exist, test whether the state improves prediction
+*conditional on* Warning. If it does, a fitted and calibrated model has something
+to fit; until then there is nothing to calibrate against. Backfilling would get
+there faster: capex direction is derivable from the 10-Q/10-K capex line, which
+the SEC fundamentals import already carries, and "good news, stock down" from
+earnings dates plus next-day returns, which the Dolt earnings import already
+carries. That last one is worth computing deterministically rather than asking
+the LLM to judge, for the same reason the state derivation is rule-based.
+
 ## What changed in v4
 
 **V1 stopped saturating at VIX 30.** `(vix - 15) / 15` reached 100 at VIX 30 —
@@ -81,6 +237,16 @@ a qualitative overlay reported beside the scores. Capex also stopped scoring
 `raising` and `holding` identically at 0: `holding` is the deceleration case and
 now scores 50, so a boom no longer reads the same as a stall.
 
+> **Corrected 2026-08-12.** The claim in this paragraph is false. "Pegged
+> they produced a Warning of exactly 20.0" describes only the case where every
+> technical sensor reads zero; Warning is a weighted average, so in the general
+> case those 20 points added +10 to +20 and moved the technical score needed to
+> reach the 40 quadrant divider from 40 to 25. The observation was removed for
+> being *underweighted*, on reasoning that mistook a corner case for the whole
+> range. See "The fundamental channel" above for what replaced it — a separate
+> categorical channel, not a restored weight. The capex `holding` rescale in the second half
+> of this paragraph stands and is still live.
+
 **The drawdown sensor stopped saturating.** v2 used `dd_pct * 5`, reaching 100 at
 a 20% drawdown — the 90th percentile of the observed distribution. 39 of 408
 sessions sat at exactly 100 with no resolution left, and the price pillar showed
@@ -126,7 +292,11 @@ upper half of the Warning axis was unreachable.
 - 60-session SMH/SPY relative-strength deterioration, 30%.
 - HY OAS 20-session widening, 25%.
 
-Combined, RSP/SPY (former F4), and the NVDA canary (former P6) do not enter v3 or v4.
+**Fundamental context** — a categorical third channel, not a term in either
+score. See "The fundamental channel" above.
+
+Combined, RSP/SPY (former F4), and the NVDA canary (former P6) do not enter v3
+or v4.
 
 ## Calibration
 
@@ -279,31 +449,73 @@ reseed exists to close. The history API and main chart show only snapshots match
 the current methodology, so a bump reseeds the series rather than splicing two
 formulas into one line.
 
-The fundamental overlay keeps its effective date (normally the next session after
+The fundamental channel keeps its effective date (normally the next session after
 collection) and is never replayed backward, so a rebuild cannot stamp today's
-observation onto historical snapshots. Because the observation is stored in a
-single slot, a refresh replaces the previously effective record: the snapshot
-therefore reports the overlay as `pending` until the new effective date.
+observation onto historical snapshots. Since the observations became a real
+series (`regime_fundamental_observations`, migration 033), the effective-date
+lookup *is* the gate: a replayed session gets whichever observation was live on
+it, and sessions before the first one read `unknown`.
 
-Two functions, deliberately: `fundamental_overlay` is the **record** and keeps
+Two functions, deliberately: `fundamental_context` is the **record** and keeps
 the gate — it runs for every replayed date during a rebuild, so it must never
 grow a bypass flag. `current_observation` is the **live reading** behind
-`fundamental_context`, and *reports* the effective date instead of blanking the
+`fundamental_live`, and *reports* the effective date instead of blanking the
 content.
 
 Until 2026-08-07 the live reading called the gated function, so a just-collected
 observation stayed hidden until the next weekday — three days over a weekend —
 and refreshing appeared to do nothing. That was the opposite of what this section
-already claimed. Showing it early cannot leak into a published number, because
-nothing in the overlay is scored (see "Fundamentals left the score").
+already claimed. Showing it early cannot leak into a published score, because
+nothing in the channel is scored.
 
 `current_observation` gates on `observed` (a non-null `fetched_at`, the one field
 every path writing real content stamps). Without it, the default override —
-`unknown` for every hyperscaler and `mixed` for the reaction — was reported as a
-live observation with `available: true`, so the card presented placeholders as a
-collected reading. Those are the absence of an observation, not an observation of
-absence. `fundamental_overlay` never had this problem: no observation means no
-effective date, which means `pending`, which already blanks the content.
+`unknown` for every hyperscaler and, since 2026-08-13, `unknown` for the reaction
+— was reported as a live observation with `available: true`, so the card
+presented placeholders as a collected reading. Those are the absence of an
+observation, not an observation of absence. `fundamental_context` never had this
+problem: no observation means no effective date, which means `pending`, which
+already blanks the content.
+
+**`usable` is what may confirm; `available` is only what to display.** Three
+distinct things, and collapsing any two of them is a bug:
+
+- `state` — the last thing observed. Survives going stale, so the card can show it.
+- `available` — *timing*: there is an effective, non-stale record to display.
+- `usable` — *content*: available **and** the observation actually determined
+  something (`state != "unknown"`).
+
+The confluence alert and all three coverage-matched study rules gate on `usable`.
+Gating on `available` instead has two failure modes, and both were live at some
+point in this design:
+
+1. a reading past `fundamental_staleness_days` would corroborate every Warning
+   crossing indefinitely — the strongest claim this channel makes, from the data
+   with the least right to make it;
+2. an LLM run that failed to extract anything produces a perfectly fresh
+   observation that knows nothing. Counting it as exposure means repeated
+   extraction failures slowly accumulate coverage until the fundamental rows flip
+   to a *measurable* 0/8 — a failed result published for a channel that never saw
+   a thing, which is precisely what coverage-matching exists to prevent.
+
+**Pre-rename snapshots are adapted, not discarded.** The channel was stored as
+`fundamental_overlay` until 2026-08-12. The rename shipped without a methodology
+bump — no score changed — so those rows are still served and were never reseeded.
+Reading only the new key would have turned every one of them into `unknown`,
+silently dropping real recorded evidence: historical Path colours, and exposure
+the event study can legitimately count. `_parse_snapshot` derives the channel
+from a legacy overlay's own stored facts (its capex map supplies the basket, so
+the derivation uses the names observed at the time rather than today's config).
+Normalising there rather than at each call site means no reader can receive an
+un-adapted row. Delete only after a reseed has rewritten the whole window.
+
+**The blob and the series row are one transaction.** They are the same
+observation seen by the live card and by the point-in-time replay; committing
+them separately leaves a window where a failure publishes one and not the other,
+and the two then disagree permanently with nothing to detect it. Both writers use
+`settings_store.upsert_setting` (which does not commit) plus a single commit;
+`record_fundamental_observation` deliberately takes no commit of its own so
+`update_regime_monitor` keeps its own transaction boundary.
 
 Each snapshot stores the fixed basket symbols, hash, and freeze date.
 Reconstructed history before that freeze date is retrospective/exploratory.
@@ -321,39 +533,185 @@ today's number. The quadrant dividers rendered in Path view come from
 
 ## Warning study
 
-The study calls the outcome a **10% correction**, not a regime break. The first
-70% of sessions freezes the 80th-percentile warning threshold; alarm episodes are
-measured on the final 30%. Because v3 dropped fundamentals from the score, the
-study now measures exactly the live Warning score rather than a technical-only
-approximation of it, and both are computed from one shared sensor definition
-(`warning_sensor_scores`) so they cannot drift apart.
+The study calls the outcome a **10% correction**, not a regime break. It measures
+two rules against that outcome, plus enough context to tell whether either number
+is any good.
 
-A cached report is discarded when its methodology no longer matches, so the panel
-reverts to "not run yet" after a bump rather than showing stale numbers. **Re-run
-the Event Study job after cutting over to v4.**
+A cached report is discarded when its methodology no longer matches *or* when
+`STUDY_SCHEMA` moves, so the panel reverts to "not run yet" rather than showing
+stale numbers or a report missing half its blocks. **Re-run the Event Study job
+after a methodology cutover or a schema bump.**
+
+### The headline is the rule that actually fires
+
+Until 2026-08-12 the study measured a bare rising-edge crossing of an
+80th-percentile threshold fitted on the first 70% of sessions. **Nothing consumes
+that rule.** What reaches Telegram is `_collect_regime_quadrant`: a quadrant
+change with State ≥ 50 and Warning ≥ 40 as fixed dividers, a ±5 hysteresis
+deadband, a two-session confirmation, a 3-day cooldown, and a 75% coverage gate
+on both axes. The two differ on every one of those axes, including the threshold
+itself (a fitted ~32 against a shipped 40).
+
+`replay_quadrant_changes` replays the shipped state machine over the whole
+sample. Three details are reproduced rather than cleaned up, because a state
+machine written from first principles gets each of them wrong:
+
+- the prior session is classified against the **current baseline**, not against
+  its own predecessor, so confirmation asks "did yesterday already look like this
+  change" rather than "did yesterday change too";
+- the baseline advances only when an alert actually fires, so a change blocked by
+  confirmation or cooldown is re-evaluated against the old quadrant next session;
+- one cooldown is shared by every quadrant change, so a 3→4 alert can swallow a
+  4→2 alert three days later.
+
+Two consequences worth stating. The alarm is dated at the **confirmation**, not
+at the first crossing, which costs one session of lead by construction. And the
+rule alerts on changes in both directions, so the replay's exits are recorded but
+filtered out by `entry_alarms` — only entering a Warning-high quadrant is a
+warning about anything.
+
+The replay reuses `_compute_index` rather than re-deriving the axes. That is the
+same anti-drift argument that produced `warning_sensor_scores`: the v2 study
+re-derived Warning by hand and would have kept measuring the old construct
+through a scoring change. State has no equivalent shared helper, so the snapshot
+builder itself is the shared definition.
+
+**Nothing is fitted, so nothing needs protecting from a training set.** There is
+no split, and every detected correction is evaluable instead of the four that
+happen to land in the last 30%. The `underpowered` and "threshold frozen on a
+different construct" caveats do not apply to this variant.
 
 ### Reading the result
 
-The report carries a `reliability` block and the UI renders its warnings, because
-the headline numbers invite over-reading in two specific ways.
+A bare "2 of 4" is unreadable in either direction, so the report scores four more
+rules through the same `evaluate_alarms` harness over the same events and
+sessions, and adds a null. All use fixed thresholds — a threshold fitted on the
+full sample would have lookahead the shipped rule does not, and one fitted on a
+split could only be scored on the holdout events.
+
+| kind | rules | the question |
+|---|---|---|
+| ablation | Warning ≥ 40 bare, State ≥ 50 bare | does the quadrant machinery earn its place? |
+| baseline | leader below its 50-DMA, VIX ≥ 20 | does the score earn its complexity? |
+| null | K random alarms at the observed firing rate | is any of this better than chance? |
+
+The two kinds must not be read as one list. If a baseline matches the score, the
+composite is not earning its complexity and that is the finding — it does not
+mean the monitor is worthless, since State and Warning exist to be *read*, but it
+caps how much further calibration is justified. If the bare Warning crossing
+beats the shipped rule, the machinery (not the sensor) is what is costing recall.
+
+The null draws only from sessions a rule could actually have fired on. Over the
+whole sample it would be diluted by warm-up sessions and would understate what
+chance achieves — which matters, because with ~11 events and a 20-session horizon
+roughly a sixth of the sample already sits inside a hit window. It is seeded, so
+a re-run cannot move the report. Corrections cluster and uniform placement does
+not, so it is the **floor, not the bar**: an alarm process that clustered would
+beat it for reasons unrelated to foresight.
+
+### First result (2026-08-12): the shipped rule is not distinguishable from chance
+
+Replayed over 2021-07-14 → 2026-08-12. The 200-DMA warm-up means the baseline
+only seeds on 2022-05-26, so 1056 of 1276 sessions are evaluable and 10 of the 11
+detected corrections fall inside them.
+
+| rule | kind | warned | FA/yr | median lead |
+|---|---|---|---|---|
+| **Quadrant alert (shipped)** | | **1/10** | **0.9** | 19d |
+| Quadrant alert, both axes high | ablation | 0/10 | 0.9 | — |
+| Warning ≥ 40, bare crossing | ablation | 3/10 | 4.8 | 20d |
+| State ≥ 50, bare crossing | ablation | 0/10 | 0.7 | — |
+| SMH below its 50-DMA | baseline | 7/10 | 6.7 | 8d |
+| VIX ≥ 20 | baseline | 4/10 | 7.2 | 9.5d |
+| Random alarms, same firing rate | null | 0.9 ± 0.8 | — | — |
+
+**P(chance ≥ 1/10) = 0.65.** Alarms scattered at random over the same sessions at
+the rule's own firing rate match or beat it two times in three. Whatever the
+score knows, this rule is not transmitting it.
+
+Three readings, in order of how much they should change:
+
+**The machinery costs more than it protects.** The bare Warning crossing catches
+3 with a 20-session lead; wrapping it in the quadrant rule drops that to 1. The
+State condition is the largest single cost — requiring both axes high catches
+nothing at all, which is what a coincident axis gating a leading one predicts.
+Hysteresis, the two-session confirmation and the shared cooldown between them
+take the rest, and the cooldown is shared across *every* quadrant change, so
+exits consume the budget that entries need. Only 5 of the 15 replayed changes are
+Warning-high entries.
+
+**The crude baselines beat everything on recall, at a price.** SMH below its
+50-DMA catches 7 of 10 — but at 6.7 false alarms a year against the shipped
+rule's 0.9. That is a 7× recall improvement for 7× the noise, so it is not a
+clean dominance and this table cannot settle it; the missing axis is what a false
+alarm actually costs, which nothing here measures. What it does settle is that
+the composite is not buying recall the 50-DMA does not already have.
+
+**The 0.9 false alarms/year is not the achievement it looks like.** A rule that
+almost never fires has few false alarms by construction. Read the two columns
+together or not at all.
+
+Recorded from an offline replay (live Alpaca + FRED, no database, breadth
+computed from the same Alpaca closes rather than the stored universe). The job in
+Admin → Jobs is the canonical path and reads breadth from the DB, so re-run it to
+confirm these figures before treating them as the record.
+
+**This is a verdict on the market channels only.** The fundamental and confluence
+rows in the same table are marked `measurable: false` and print "not measurable"
+rather than a ratio: with an empty observation series they never fire, and a 0/10
+sitting in a comparison column would read as tested-and-failed. `false` here means
+the input does not exist yet, not that the rule lost.
+
+(The figures above were also produced under a briefly-built weighted modifier and
+came back bit-identical, which is what confirmed the modifier was inert over the
+whole window — the numbers depend on the technical sensors alone either way.)
+
+**Not acted on.** Nothing in the alert path was changed on the strength of this.
+The obvious candidates — dropping the State condition from the entry test,
+separating the entry and exit cooldowns, or lowering the Warning divider — are
+threshold changes to a live alerting rule and want their own decision.
+
+### The coverage gap relocates, it does not close
+
+Dropping the fitted threshold makes the whole sample evaluable, but most of the
+extra events predate 2023-08. W3 does not exist there, so Warning renormalises to
+`(W1×45 + W2×30)/75` and the fixed 40 divider is applied to a different construct
+than it was reasoned about. The report therefore splits shipped-rule metrics at
+the credit sensor's first session and the panel states both, because replacing
+one misleading headline with a differently misleading one would be no gain.
+
+Convenient side effect: the pre-credit era *is* the "Warning without W3"
+ablation, measured on real sessions rather than simulated ones, so that ablation
+is not run separately.
+
+Alarms and events are assigned to eras by index, so an alarm days before the
+boundary matching an event days after it lands in the earlier era. With the eras
+years long and the events sparse, that costs nothing.
+
+### The fitted variant, kept for continuity
+
+The 70/30 percentile study is still computed and still reported, collapsed, with
+its `reliability` block intact — it is a genuinely different question, and it is
+what earlier revisions of this document report. Its caveats stand:
 
 **The holdout is thin.** The study detects 11 corrections across 5 years but the
-70/30 split leaves only 4 in the test period. Recall is therefore one event away
-from a materially different headline, and in practice the event that flips is
-decided by where the frozen threshold happens to land rather than by whether the
-score saw anything. The v3 cutover run illustrates it: v3 scored 2/4 against v2's
-3/4, but "v3 without the credit sensor" scores 3/4 at a *higher* threshold
-(35.5) than shipped v3 misses it at (32.3) — because the alarm rule needs a
-rising edge, and a lower threshold can mean the alarm already fired outside the
-20-session horizon and never reset below. Below `MIN_EVENTS_FOR_CONFIDENCE`
-holdout events the report says so explicitly.
+70/30 split leaves only 4 in the test period. Recall is one event away from a
+materially different headline, and in practice the event that flips is decided by
+where the frozen threshold happens to land rather than by whether the score saw
+anything. The v3 cutover run illustrates it: v3 scored 2/4 against v2's 3/4, but
+"v3 without the credit sensor" scores 3/4 at a *higher* threshold (35.5) than
+shipped v3 misses it at (32.3) — because the alarm rule needs a rising edge, and a
+lower threshold can mean the alarm already fired outside the 20-session horizon
+and never reset below. Below `MIN_EVENTS_FOR_CONFIDENCE` holdout events the
+report says so explicitly.
 
 Some events carry no information at all for comparison: in that run every
 variant caught 2026-03-06, every variant missed 2026-06-05, and every variant
 "caught" 2025-11-20 with a 1-session lead, which is coincident rather than a
-warning.
+warning. The headline recall does not currently discount those; a minimum-lead
+rule is the obvious next change and has not been made.
 
-**Sensor coverage can straddle the split.** The score renormalises over available
+**Sensor coverage straddles the split.** The score renormalises over available
 sensors, so a training window predating a sensor's history freezes the threshold
 on a different construct than the holdout is measured against. At the v3 cutover
 only 39% of training sessions had all three Warning sensors versus 100% of the
@@ -362,9 +720,22 @@ test period, because credit history begins 2023-07-25.
 Restricting the threshold to sensor-matched training sessions was tried and is
 *not* the fix: those sessions are a calm recent stretch, so the threshold drops
 from 32.3 to 22.5 and false alarms rise from 3.3 to 8.6 per year. It trades a
-coverage bias for a regime-selection bias. The honest position is that the
-threshold is hypersensitive to window choice at this sample size; the report
-states its limits rather than pretending to a precision it does not have.
+coverage bias for a regime-selection bias. The honest position is that a fitted
+threshold is hypersensitive to window choice at this sample size — which is the
+strongest argument for making the unfitted shipped rule the headline.
+
+### Considered and not done
+
+**An ETF credit proxy (HYG/IEF) to extend W3 back over the whole sample.** It
+would trade "two sensors versus three" for "proxy sensor versus real sensor" —
+still a construct straddle, but no longer flagged by the coverage split. This is
+the same objection that rejected `BAA10Y` as a percentile reference. If ever
+revisited, check the impulse correlation on the three years of real-OAS overlap
+first and report it as a sensitivity, never as the headline.
+
+**A depth sweep (5%/7%/15% corrections) for more events.** `EVENT_COOLDOWN_DAYS`
+is 40, so at shallower thresholds re-triggers inside a single decline merge or
+drop and the denominator moves for cooldown reasons rather than market ones.
 
 ## Resolved in v4 (raised 2026-08-07, shipped 2026-08-08)