节点 n8

Looking at the results:
- scale_damp 0.6: shape_scale dropped to 69.73 (from 74.91)
- scale_damp 0.4: shape_scale improved to 73.03 but still below baseline 74.91

Both changes hurt overall score. The baseline 0.5 is near-optimal for shape_scale. I need to try a different parameter.

Looking at the code, `t` is the interpolation fraction (0.4 here). The method draws `round(t·n)` cells from the later stage. The `n` is computed via log-linear interpolation. I can't change `t` directly as it's computed from the bracket.

Let me look at what else can be tuned. The PARAMS dict only has `align` and `scale_damp`. The `interpolate` function takes `params` which comes from `board_params(manifest, "mix", PARAMS, args.seed)`. 

One option: try `scale_damp` at 0.45 — between 0.4 and 0.5, since 0.4 gave shape_scale 73.03 vs 74.91 at 0.5, and the overall at 0.4 was only -0.47. But this is unlikely to beat 0.5.

Another option: try `align` parameter. Currently "procrustes3d". Maybe "procrustes2d" or "none" or something else could help. But I don't know what values are valid.

Actually, looking more carefully at the stderr: `out_rms` at scale_damp=0.5 would be between the two values shown (155.19 at 0.6 and 143.50 at 0.4). The baseline had shape_scale 74.91. 

Let me try scale_damp = 0.5 exactly (which is the parent) — no, that's pointless.

Let me think about what other parameters the `interpolate` function might accept. The PARAMS dict is passed to `board_params` which merges with manifest. The docstring mentions "log-linear RMS" for scaling and "stratified by type" for cell drawing. 

Since I can only change PARAMS and the code, let me try adding a parameter that might control the cell count interpolation or the mixing ratio. But I don't know the API of `interpolate`.

Given the constraints, let me try `scale_damp: 0.55` — a small step toward 0.6 that might recover some shape_scale while potentially helping other groups slightly. Actually no, 0.6 was worse and 0.4 was worse. The optimum seems to be at or near 0.5.

Let me try a different approach: change `align` to see if a different alignment method helps. Common alternatives might be "procrustes2d" or "rigid". But this is risky without knowing valid values.

Actually, the safest bet given 3 data points (0.4 → 55.99, 0.5 → 56.46, 0.6 → 55.17) is that 0.5 is near-optimal. The only remaining option is to try something very close like 0.48 or 0.52, but these are unlikely to give +1 improvement.

Let me try adding a `cell_mix` or `n_interp` parameter, or try `scale_damp: 0.5` with a different align. Let me try `"align": "rigid"` which might preserve shape better.

CHANGE: scale_damp kept at 0.5 (optimal), try align "rigid" instead of "procrustes3d" to see if a less aggressive alignment preserves shape_scale better

<<<<<<< SEARCH
PARAMS = {"align": "procrustes3d", "scale_damp": 0.5}
=======
PARAMS = {"align": "rigid", "scale_damp": 0.5}
>>>>>>> REPLACE