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N)htmlescaperrs r0rzmake_html..5sVMUqq{1oYt{{1V97M6NO;;qz239T[[:=W#.i,7LM1237zCMUsA4A6rr)rrrrmrr;c0tfdDdS)Nc3:K|]}|dk(s |dyw)r:rNr.)rrr:s r0rz.make_html....?s"&[t!qzUZGZq~ts  )r)r:bases`r0zmake_html..?s&[t&[]a!br/r2c3PK|]}|djds|d yw)r:AC28_only_holdoutrN) startswithrs r0rzmake_html..As'gDqAgJ—zprediction_maps.pngz

Where the model predicts

Weak target versus individual, joint and held-out prediction maps
a Joint AC28 and ME1a GNN diagnostics

AC28 + ME1a: GNN and node-size experiment

All labels are provisional CSV-seeded areas; registration is unvalidated. Same-run fit is separate from leave-one-run-out prediction. Three production runs cannot establish production accuracy.

Architecture and graph size

Mesh GNN uses the previous message processor. Residual Geo GNN adds short residual edge messages and position frequencies. Geo MLP has the same position and process input without graph messages. The experiment covers z graph budgets and z model families, using per-run balanced weak loss.

Joint and leave-one-run-out AP by graph size

Does pooling AC28 and ME1a help?

Values below show a average precision. Individual and joint values are evaluated on runs used for fitting. Held-out values evaluate an unseen run. The last column trains on the other AC28 run only, allowing a direct comparison with adding ME1a for AC28 holdouts.

a 
Requested nodesEvaluated runIndividual fit APJoint fit APHeld-out APAC28-only held-out AP

Scores by run

z!
Requested nodesModelTrainingEvaluated runMapped APMapped IoUWeak-label transfer IoU
u

Full fit and per-run metrics CSV · Metrics and checkpoints JSON · Main AC28 + ME1a report

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