The score was computed and then thrown away - carried on the per-image message but transported
nowhere - so the automation it exists for could not read it. It now flows like bkg_estimate at
every layer: CBOR (per-image key, END-block run mean and per-image array), HDF5 (per-image
/entry/MX/spindleBlindFraction in the data files, the array and spindleBlindFractionMean in the
master), read-back into a re-opened dataset, the scan result, the receiver plots, the REST plot
and scan_result schemas, and the viewer and frontend plot menus.
Absence is load-bearing and every transport keeps it distinguishable from a measured zero: the
CBOR key is simply missing, the HDF5 array holds NaN, and read-back turns NaN back into an
absent optional rather than a value. A pipeline that read 0 where the truth is "no value" would
take exactly the wrong action - a measured 0 says one sweep loses nothing, absence says nobody
could look, and the second must engage the recovery protocol while the first must not. The
round-trip tests pin all three states through CBOR and through a written-and-reopened file.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
leonarski_fandClaude Opus 5
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