Two things, both about telling one ice quantity from another.
The ice score's spot channel had its own band half-width of 0.02 A^-1 while the spot finder marks
ice rings at 0.03 (ice_ring_width_Q_recipA). The 0.02 was justified by a 5 pp specificity gain
measured on the PYTHON PROTOTYPE, which used a fitted beam centre and a mask-derived coverage table;
the shipped port, which takes the geometry's centre and the azimuthal profile's own live pixel
count, does not reproduce it. Measured over the corpus by truth class rather than by directory
label, at 0.02 vs 0.03 on the combined score: ice loops 62.13/62.19%, _icy protein 89.03/89.79%,
_clean protein 16.51/16.31%, water 17.19/20.03%. The widths are indistinguishable except on water,
where one of the four loops is independently known to carry a full hexagonal pattern. So the width
is now a parameter and the pipeline's own value is passed in - one band width, not two. The 0.012
tolerance in the radial channel is NOT a second band width, and is renamed CENTRE_SMEAR_Q to say so:
it is how far either side the channel looks for the bin a mis-set beam centre moved the ring to.
The rest is naming. Three kinds of number were all called score, or built from things called count,
and a reader could not tell from the name whether 1 meant "none" or "certain" - which are opposite.
The convention, now stated in docs/CPU_DATA_ANALYSIS.md: *_score is bounded [0,1] and 1 is
certainty, *_ratio is unbounded and 1 is nothing, *_count is a count. The C++ identifiers for the
ice ring ratio follow it (ice_ring_score -> ice_ring_ratio, GetIceRingScore -> GetIceRingRatio,
PlotType::IceRingScore -> IceRingRatio), and the local in the scaling gate that shadowed the new
ice_score while meaning the ring ratio is renamed with them.
Nothing outside the source moved: the CBOR keys ice_ring_score and ice_ring_score_mean, the datasets
/entry/MX/iceRingScore and iceRingScoreMean, the ice_ring_score plot type and the --ice-min-score
flag are all unchanged, and were checked to be after the rename. Renaming those changes stored
files, the stream format, the REST API and a CLI flag, and is a separate decision.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
proteinScore and iceScore are saturating scores in [0,1] that answer presence, not quality: a superb
crystal and a barely-diffracting one both read near 1, and neither the spot count nor the resolution
enters either of them as a term. iceRingScore already reports a magnitude - a ratio, unbounded - which
is not a number that can be thresholded; these are.
The protein score counts distinct d SHELLS above 5 A rather than spots, so a parasitic ring in the
low-resolution band cannot accumulate evidence, and weights each spot against the frame's own median
so a scattering of the weakest detections cannot fill a shell either. The ice score carries two
channels and takes the stronger: a radial one over the azimuthal profile, which runs the hexagonal
and the CUBIC phase as separate hypotheses and decides between them at the end (flash-cooled loops
show cubic or stacking-disordered ice at least as often as hexagonal, the two share only three
lines, and dropping the cubic hypothesis costs about 5 pp on iced loops), and a spot one that reads
an excess on the ice radii against the same band slid to every ice-free offset, which is what
catches ice arriving as discrete crystallites and leaving the radial profile flat.
Both read d out of the geometry, so both move with a beam-centre error; the centre is not fitted
here, and the one they were computed with is written beside them as scoreBeamCenterX/Y so a later
rescoring can tell an algorithm disagreement from a geometry one.
Ported from validated prototypes and checked against them frame by frame on stored data: mean
absolute difference 2.7e-5 (protein), 1.3e-8 (ice radial) and 3.4e-4 (ice spots). On a 41-loop
battery the protein score reaches 98.4% of confirmed-protein frames and 0.00% of water frames, and
finds no cluster on any water or ice raster. Cost is 0.01 ms/frame for the protein score and
0.08-0.32 ms/frame for the ice score.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
leonarski_fandClaude Opus 5