docs: scope PR #25 gate_metric as opt-in example, not default

Move the soft/mixed gate-metric configuration introduced in PR #25 out of
the base default config and into a standalone example config so that
default SkillOpt runs (and paper reproduction) remain bit-for-bit on the
original hard gate.

- configs/_base_/default.yaml: drop gate_metric / gate_mixed_weight keys.
  The trainer's cfg.get("gate_metric", "hard") fallback preserves the
  original behavior unchanged.
- configs/examples/soft_gate.yaml: new standalone reference config with
  a header explaining when to consider it (small selection split with
  continuous rewards) and when not to (paper reproduction, large or
  binary-reward settings).
- README.md: add a short "Community-contributed configs" section that
  clearly flags this as user-contributed and non-default.

configs/_base_/default.yaml

@@ -71,12 +71,6 @@ optimizer:
 
 evaluation:
   use_gate: true
-  # gate_metric: 'hard' (default, backward-compatible),
-  #              'soft' (use soft/F1 score),
-  #              'mixed' ((1 - w) * hard + w * soft).
-  # See skillopt/evaluation/gate.py for details.
-  gate_metric: hard
-  gate_mixed_weight: 0.5
   sel_env_num: 0
   test_env_num: 0
   eval_test: true