BioMixQA

Overview

BiomixQA is a curated biomedical question-answering dataset designed to evaluate AI models on biomedical knowledge and reasoning. It has been utilized to validate the Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) framework across different LLMs.

Task Description

Task Type: Biomedical Multiple-Choice Question Answering
Input: Biomedical question with multiple answer choices
Output: Correct answer letter
Domain: Biomedical sciences, healthcare, life sciences

Key Features

Curated biomedical questions from diverse sources
Tests medical and biological knowledge comprehension
Validates RAG framework effectiveness for biomedical domain
Multiple-choice format for standardized evaluation
Useful for evaluating healthcare AI systems

Evaluation Notes

Default configuration uses 0-shot evaluation
Simple accuracy metric for performance measurement
Evaluates on test split
No few-shot examples provided

Properties

Property	Value
Benchmark Name	`biomix_qa`
Dataset ID	extraordinarylab/biomix-qa
Paper	N/A
Tags	`Knowledge`, `MCQ`, `Medical`
Metrics	`acc`
Default Shots	0-shot
Evaluation Split	`test`

Data Statistics

Metric	Value
Total Samples	306
Prompt Length (Mean)	344.93 chars
Prompt Length (Min/Max)	316 / 393 chars

Sample Example

Subset: default

{
  "input": [
    {
      "id": "5e830918",
      "content": "Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B,C,D,E.\n\nOut of the given list, which Gene is associated with head and neck cancer and uveal melanoma.\n\nA) ABO\nB) CACNA2D1\nC) PSCA\nD) TERT\nE) SULT1B1"
    }
  ],
  "choices": [
    "ABO",
    "CACNA2D1",
    "PSCA",
    "TERT",
    "SULT1B1"
  ],
  "target": "B",
  "id": 0,
  "group_id": 0,
  "metadata": {}
}

Prompt Template

Prompt Template:

Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.

{question}

{choices}

Usage

Using CLI

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets biomix_qa \
    --limit 10  # Remove this line for formal evaluation

Using Python

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['biomix_qa'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)

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