refactor(g05): keep recipe runtime unchanged

docs/source/language_and_recipes.mdx

@@ -146,24 +146,6 @@ The renderer does not apply a tokenizer chat template. Policy processors decide
 Blend recipes select one weighted sub-recipe deterministically from the sample index.
 `recipes/subtask_mem.yaml` trains the compact core blend — high-level subtask prediction, low-level execution, and memory. `recipes/subtask_mem_vqa_speech.yaml` is the fuller variant that also adds VQA and spoken interjection responses.
 
-Message turns can set `dropout` to a probability between `0` and `1`. Dropout is
-deterministic for a given sample index and independent between turns. Combine it
-with `if_present` to sample optional supervision formats while gracefully
-skipping annotations that are unavailable:
-
-```yaml
-messages:
-  - { role: user, content: "${task}", stream: low_level }
-  - {
-      role: assistant,
-      content: "${subtask}",
-      stream: low_level,
-      target: true,
-      if_present: subtask,
-      dropout: 0.5,
-    }
-```
-
 A message recipe with a supervised assistant turn on the `low_level` stream trains
 the π0.5 paper's joint sequence instead of a blend: the target span gets text CE
 while also conditioning the action losses in the same forward.