The neighbour SAP-divergence cohort was (postcode, property_type, built_form),
which mixed electric- and gas-heated dwellings. Electricity scores materially
lower in SAP than mains gas for identical fabric, so a mixed-fuel postcode
produced cross-fuel false outliers — an electric dwelling flagged only for being
electric among gas neighbours.
Add the main-heating fuel class to the cohort key (electricity variants — 29/30
+ off-peak 31-40 — collapse to one class; every other code is its own bucket).
Now every flagged divergence is a same-fuel comparison worth investigating. On
portfolio 814 this refined 20 raw divergences to 17 same-fuel ones while keeping
the genuine within-fuel outliers (e.g. the all-electric WC2B 4AW flats at SAP
26/38 vs a cohort median of 67).
Reaches the fuel via epc_main_heating_detail through the indexed property_id —
still never touches the recommendation table. Surfaced by the portfolio-814
recommendation audit (Work item B, #1388).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Script takes an optional --scenario to restrict to one scenario's plans. New
skill drives the full loop: run the deterministic scan, review groups,
deep-dive samples via run_modelling_e2e, characterise sub-classes, and
cross-reference open PRs/ADRs — then proposes new checks to codify.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
