Correction 1: 38.8's A/B scores every arm under stock urb, which is only
sound if stock is ground truth -- and stock is what this section shows is
miscalibrated. Scoring the repair under the objective it repairs penalises
it for repairing. That result is not evidence against usage_daylight.
The measurement that matters needs no search: are the emitted failures
true? audit_crinkliness_truth.py classifies every stock crinkliness fail by
the leaf's declared usage. 164 of 271 (61%) are reported against spaces
that want no daylight -- stores, WCs, plant, corridors, covered courtyards
-- and it holds on evolved artefacts (maple generated.dom: 64%), not just
constructed seeds. Under value *= 0.5 ** len(failures) each one halves the
fitness of a design that did nothing wrong.
Correction 2: usage: is the wrong key, and usage_daylight as written
mis-keys it. 39.7 established usage: as an ACCESS-requirement class.
"Needs no special access" and "needs no window" are different questions,
and the corpus separates them: usage: none is Waiting Room, Reception,
Reception Office, Entrance Foyer -- a waiting room plainly wants daylight
and DAYLIGHT_USAGES exempts it. The usage: bedroom half is right, but by
luck of where the access axis happened to fall.
The audit is robust to that error (61% -> 57% if none is reclassified), so
the finding stands; the design does not. Daylight needs its own declared
per-space axis, decided by the programme author as usage: was.
usage_daylight stays default off and is not the shipping fix. The
compact-side clip is the right shape for the factor, so the mechanism is
retained pending a daylight: attribute to key it on.
Higher-power A/B stopped: it was chasing a score against a flawed objective
with a mis-keyed fix.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
Fixed-budget A/B (3000 evals, 3 seeds, harbor + maple, every arm scored
under stock urb so the permissive modes cannot win by deleting a fail
category).
usage_daylight's paired hard-fail deltas are harbor [0,-1,-10] and maple
[0,+2,-10]. The means (-3.7, -2.7) flatter it: the whole signal is seed 2
in both programmes, and seed 2 is the seed where stock itself does worst.
Two seeds in three are flat or slightly worse. On that seed soft rises as
much as hard falls (harbor -10h/+9s, maple -10h/+15s), so totals go
62->61 on harbor and 120->125 on maple.
Because the scoring is stock, that is a genuine trade of hard failures for
soft ones, not a relabelling -- progress under the tiered comparator, where
n_hard is primary, but a fail against this issue's acceptance criterion
("without inflating soft"). Which yardstick is right is now the live
question, and it is gvb's question as much as ssz's.
usage_daylight stays default off; undecided, not refuted. Higher-power run
(urb vs usage_daylight, 10 seeds) is running.
The diagnostic half stands independent of the search A/B: the objective
demands daylight of two thirds of the buried population that does not want
it, and 38.6's contrary null was an artefact of three modes that never
touched those leaves.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
fitness.py already imports the module as `_programme` at the top and uses
that idiom elsewhere (`_programme.SOCIABLE_USAGES`). The local re-import
sat in the per-leaf hot path for no reason.
Also snapshots the in-progress ab_ssz_search.csv; the full run is still
going and will supersede it.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
DESIGN.md 38.6 concluded the three crinkliness modes were inert against the
circulation-deletion incentive. Two things were wrong with that measurement.
Its premise, 38.2, is retracted. And its script selected leaves with the
pre-39.4 prefix rule `type[:1].upper() in ("C","O")`, which sweeps every
programme room starting with c or o -- cr1, of1 -- in as circulation.
The simpler problem is that none of the three modes ever touched the leaves
ssz is about. quality_uncrinkliness reaches `if not crink` before any mode
logic that matters, so for a zero-exposure leaf: floor returns 0.01 (one
percent of a unit quality, multiplied into a product and weighed against a
whole leaf's cost -- inert); compact_ok is self-contradictory, announcing
that compact is not a defect and then returning the floor for the most
compact case of all; exempt_circulation reaches at most a third of them.
Measured: 0% / 0% / 0% / 21-33% of buried leaves rescued.
What the buried leaves are, now that 39.7 gives every space a usage: two
thirds of them are spaces that architecturally do not want a window --
stores, WCs, plant, corridors, covered courtyards -- scored identically
with a windowless bedroom. harbor 22/33, maple 33/46, health 9/18.
- crinkliness_mode="usage_daylight": daylight required of the uses a
person occupies (programme.DAYLIGHT_USAGES) and nothing else. Elsewhere
the factor is clipped on the compact side only, so being buried stops
being a defect while over-exposure still costs -- a crinkly leaf costs
envelope whatever it is used for. A windowless bedroom stays the hard
zero it is under stock: 11/11, 13/13, 9/9 still failing.
- compact_ok repaired to score the buried limit as compact, the behaviour
its name always claimed. It now rescues 100% including bedrooms, and is
kept as the upper-bound control, not a candidate.
- ab_ssz_search.py: the fixed-budget search A/B ssz's acceptance criteria
actually asks for. Every arm is optimised under its own objective and
re-scored under stock urb, because the permissive modes return 1.0
where stock fails and would otherwise win by deleting a fail category.
- ab_crinkliness_mode_ssz.py: prefix rule fixed, retracted premise
flagged in its docstring.
- 38.7's remaining claims from the retracted 38.2/38.3 corrected.
Default is unchanged ("urb"), byte-identical to all prior runs. Lint at
parity (46 pre-existing); tests 366 passed, 10 new, same 7 pre-existing
fixture failures (homemaker-py-bdf).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
CP-SAT assignment does not clearly beat greedy end-to-end: worse on
harbor-house hard fails, roughly a wash on maple-court, and the reassign
operator fired in only 1 of 18 runs. Keeps assign_solver="greedy" and
enable_reassign=False as defaults; closes the bead's remaining acceptance
criterion. Raw results in experiments/results/.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LSwQwpEaHFBkeVSDDWd75S
