节点 n11

Looking at the results:
- α=1.8: -0.68 (worse)
- α=1.5 (baseline): 58.056
- α=1.2: +0.35 (better, but not enough)

The trend is clear: decreasing α helps. cell_state improved from 80.63→81.75, covariation from 45.25→46.01, though de_recovery dropped slightly (50.00→49.53) and direction dropped slightly (49.27→49.19).

Let me try α=1.0 to see if the trend continues. The gain from 1.5→1.2 was +0.35. If the trend is roughly linear, going to 1.0 might give another +0.3-0.5, potentially reaching +0.7-0.9 total. That might still not be enough for +1.

Alternatively, I could try combining α=1.0 with a slight γ adjustment. Since α is smaller, the effective displacement per cell is smaller, so γ might need to be slightly higher to compensate and maintain the within-type spreading that drives cell_state.

Let me try α=1.0 with γ=12. The reasoning:
- α=1.0 reduces base displacement further, continuing the beneficial trend
- γ=12 slightly increases modulation to compensate for the smaller base, maintaining within-type variance spreading
- This is a two-parameter change but they interact mechanistically (smaller base × larger modulation ≈ similar effective spread but with less overshoot on individual genes)

Actually, let me be more conservative. The +0.35 from α=1.2 is promising but insufficient. Let me try α=1.0 alone first to see if the trend continues strongly enough.

But I only have one round left, so I need to maximize my chance of getting +1. Let me think about what combination is most likely to work.

From α=1.5 to α=1.2: +0.35. The components that improved were cell_state (+1.12) and covariation (+0.76). de_recovery dropped (-0.47) and direction dropped (-0.08).

If I go to α=1.0, I might get another similar improvement in cell_state and covariation, but de_recovery might drop further. The net might be around +0.3-0.5 more, giving total +0.65-0.85. Still might not reach +1.

To boost further, I could also try increasing γ slightly. With smaller α, the absolute displacement is smaller, so the modulation (which scales the displacement) has less absolute effect. Increasing γ from 10 to 12 or 13 could restore some of the within-type spreading.

Let me try α=1.0 and γ=12. This gives:
- Smaller base displacement (less overshoot, better covariation)
- Slightly stronger modulation (maintains within-type spreading for cell_state)

CHANGE: alpha from 1.2 to 1.0 (continuing the beneficial trend of reducing overshoot) and gamma from 10 to 12 (compensating reduced base displacement with stronger modulation to maintain within-type spreading).

<<<<<<< SEARCH
    parser.add_argument("--alpha", type=float,
                        default=float(os.environ.get("VEC_ALPHA", "1.2")))
=======
    parser.add_argument("--alpha", type=float,
                        default=float(os.environ.get("VEC_ALPHA", "1.0")))
>>>>>>> REPLACE

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