The distinction between schema validity and semantic correctness is the part I’d pay the most attention to. A response can satisfy every required field and still point to a line that doesn’t exist or provide evidence that was never in the source.

I’d keep structural validation and grounding checks as separate stages, then track failures by category: malformed output, repair required, invalid references, and unsupported claims. That makes the schema-off experiment much more useful because you’re measuring not just whether the model returns valid records, but whether those records are actually reliable. Strict output controls the shape; it doesn’t establish truth.