Add BioASQ

[Ash-29]

This PR implements the BioASQ environment for large-scale biomedical semantic question answering, evaluating models' ability to generate comprehensive, expert-level answers grounded in scientific literature.

Dataset Integration: Uses the kroshan/BioASQ dataset from HuggingFace containing 5,729 biomedical questions with ideal answers and supporting evidence, following BioASQ 2025 Task 13b specifications.

Evaluation Framework: Implements LLM-as-judge evaluation with 4-dimensional scoring exactly as specified in official BioASQ manual assessment criteria:

Precision (1-5): Accuracy and relevance of biomedical facts
Recall (1-5): Coverage of important biomedical concepts
Repetition (1-5): Redundancy assessment (inverse scoring)
Readability (1-5): Clarity and professional organization
Answer Formats: Supports both XML (...) and BOXED answer formatting to match med-lm-envs conventions.

Judge Integration: Uses JudgeRubric with configurable judge models (default: gpt-4o-mini) and follows the exact async judge pattern from other med-lm-envs environments like aci_bench.

Technical Implementation: Follows all med-lm-envs patterns including proper data parsing, normalized scoring (0-1 range), CLI integration with environment-specific arguments, and comprehensive documentation with dataset examples and statistics.

[CLAassistant]

Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.

---

Ashish seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.
_{You have signed the CLA already but the status is still pending? Let us recheck it.}