---
title: MedReason-Stenographic
canonical_url: "https://www.modelscope.cn/datasets/openmed-community/MedReason-Stenographic"
md_url: "https://www.modelscope.cn/datasets/openmed-community/MedReason-Stenographic.md"
repository: openmed-community/MedReason-Stenographic
last_updated: 2026-01-10
license: apache-2.0
storage_size: "83 MB"
downloads: 72
stars: 0
---

# MedReason-Stenographic

> MedReason-Stenographic - openmed-community 在 ModelScope 开源的数据集。MedReason-Stenographic: Medical QA with Compressed Reasoning Traces

openmed-community/MedReason-Stenographic 是 ModelScope 魔搭社区上的数据集，存储大小 83 MB，采用 apache-2.0 许可。

- **Repository**: openmed-community/MedReason-Stenographic
- **License**: apache-2.0
- **Storage size**: 83 MB
- **Downloads**: 72
- **Stars**: 0
- **Last updated**: 2026-01-10

Source: https://www.modelscope.cn/datasets/openmed-community/MedReason-Stenographic

---

# MedReason-Stenographic: Medical QA with Compressed Reasoning Traces

This dataset contains **31,535** medical question-answer pairs with stenographic reasoning traces, generated using MiniMax M2.1 from the original [UCSC-VLAA/MedReason](https://huggingface.co/datasets/UCSC-VLAA/MedReason) dataset.

## Dataset Description

The dataset transforms medical QA reasoning into a **stenographic format** using a symbolic protocol designed for high-density, machine-parseable reasoning traces. This format eliminates natural language filler while maintaining the complete logical flow of medical reasoning.

### Key Features

- **31,535 samples** of medical QA with compressed reasoning (filtered for non-empty reasoning)
- **Stenographic reasoning traces** using symbolic notation
- **Full thinking process** preserved in the `thinking` field
- Based on the award-winning MedReason dataset (3rd place, HuggingFace Reasoning Datasets Competition 2025)

## Dataset Structure

### Fields

| Field | Type | Description |
|-------|------|-------------|
| `query` | string | The medical question |
| `reasoning` | string | Stenographic reasoning trace using symbolic notation (includes answer options inline) |
| `answer` | string | The final answer in unified format (e.g., "D. Urea breath test") |
| `thinking` | string | Full chain-of-thought reasoning before compression |
| `id_in_dataset` | int | Reference ID from the original MedReason dataset |

### Example

```json
{
  "query": "Most sensitive test for H pylori",
  "reasoning": "Detect(Task:RAG) ● → Domain(Gastroenterology) ● → Pathogen(H.pylori) ● → DiagnosticTests(SensitivityComparison) ● → UreaBreathTest(Sensitivity:95-98%) ● → FecalAntigen(Sensitivity:90-95%) ● → BiopsyUrease(Sensitivity:90-95%) ● → Serology(Sensitivity:80-90%) ● → DistractorAnalysis ※ → ComparativeAssessment ◐ → NonInvasiveGoldStandard ● → <H≈0.4> → ∴",
  "answer": "D. Urea breath test",
  "thinking": "The user is asking a medical question about diagnostic testing for Helicobacter pylori...",
  "id_in_dataset": 7134
}
```

## Stenographic Protocol

The reasoning traces use the **Grand Unified Reasoning Protocol (v4.1)** with the following symbolic lexicon:

| Symbol | Meaning | Usage |
|--------|---------|-------|
| `→` | Flow/Derivation | Linear progression between reasoning steps |
| `↺` | Refinement Loop | Self-correction or revisiting prior steps |
| `∴` | Convergence | Final logical conclusion point |
| `●` | Ground Truth | Verified fact from reliable source |
| `◐` | Inference | Reasoned deduction not directly stated |
| `○` | Speculation | Low-confidence hypothesis |
| `※` | Constraint/Trap | Critical rule or limitation detected |
| `⚠` | Risk/Warning | Hallucination risk or safety concern |
| `<H≈X.X>` | Entropy Marker | Cognitive shift indicator (0.1=analytical, 1.5=creative) |

### Symbol Usage Statistics

| Symbol | Samples | Percentage |
|--------|---------|------------|
| `→` | 31,419 | 99.5% |
| `∴` | 30,996 | 98.2% |
| `●` | 31,153 | 98.7% |
| `<H≈` | 27,634 | 87.5% |
| `※` | 18,045 | 57.2% |
| `◐` | 16,777 | 53.1% |
| `⚠` | 15,972 | 50.6% |
| `↺` | 9,207 | 29.2% |
| `○` | 1,622 | 5.1% |

## Dataset Statistics

| Metric | Value |
|--------|-------|
| Total samples | 31,535 |
| Unique source IDs | 10,550 |
| Avg query length | 157.4 chars |
| Avg reasoning length | 384.2 chars |
| Avg answer length | 35.2 chars |
| Avg thinking length | 5,548.4 chars |

### Data Quality

- Empty queries: 89 (0.3%)
- Empty reasoning: 0 (filtered out)
- Empty answers: 9 (<0.1%)
- All samples have thinking field populated

## Generation Process

This dataset was generated using **MiniMax M2.1** with a specialized prompt that:

1. Takes the original MedReason question-answer pairs
2. Generates full chain-of-thought reasoning (`thinking` field)
3. Compresses the reasoning into stenographic format (`reasoning` field)
4. Outputs structured JSON with query, reasoning, and answer

## Comparison with Source Dataset

| Aspect | Original MedReason | This Dataset |
|--------|-------------------|--------------|
| Size | 32,682 pairs | 31,535 pairs |
| Reasoning format | Natural language | Stenographic symbols |
| Thinking field | No | Yes (full CoT) |
| Answer format | Text only | Unified "Letter. Text" format |
| Fields | question, answer, reasoning, options | query, reasoning, answer, thinking, id_in_dataset |

## Use Cases

1. **Training reasoning models** with compressed, symbolic reasoning
2. **Fine-tuning for medical QA** with structured thought processes
3. **Research on reasoning compression** and symbolic representations
4. **Benchmarking** reasoning trace quality and consistency

## Citation

If you use this dataset, please cite:

```bibtex
@dataset{medreason_stenographic_2025,
  author = {Maziyar Panahi},
  title = {MedReason-Stenographic: Medical QA with Compressed Reasoning Traces},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/datasets/MaziyarPanahi/MedReason-Stenographic}}
}
```

Also cite the original MedReason dataset:

```bibtex
@dataset{medreason_2025,
  author = {UCSC-VLAA},
  title = {MedReason},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/datasets/UCSC-VLAA/MedReason}}
}
```

## License

Apache 2.0