Core Components: - PDFStorageService with Dify/OSS adapters - LLM12FieldsService with Nougat-first + dual-model + 3-layer JSON parsing - PromptBuilder for dynamic prompt assembly - MedicalLogicValidator with 5 rules + fault tolerance - EvidenceChainValidator for citation integrity - ConflictDetectionService for dual-model comparison Prompt Engineering: - System Prompt (6601 chars, Section-Aware strategy) - User Prompt template (PICOS context injection) - JSON Schema (12 fields constraints) - Cochrane standards (not loaded in MVP) Key Innovations: - 3-layer JSON parsing (JSON.parse + json-repair + code block extraction) - Promise.allSettled for dual-model fault tolerance - safeGetFieldValue for robust field extraction - Mixed CN/EN token calculation Integration Tests: - integration-test.ts (full test) - quick-test.ts (quick test) - cached-result-test.ts (fault tolerance test) Documentation Updates: - Development record (Day 2-3 summary) - Quality assurance strategy (full-text screening) - Development plan (progress update) - Module status (v1.1 update) - Technical debt (10 new items) Test Results: - JSON parsing success rate: 100% - Medical logic validation: 5/5 passed - Dual-model parallel processing: OK - Cost per PDF: CNY 0.10 Files: 238 changed, 14383 insertions(+), 32 deletions(-) Docs: docs/03-涓氬姟妯″潡/ASL-AI鏅鸿兘鏂囩尞/05-寮€鍙戣褰?2025-11-22_Day2-Day3_LLM鏈嶅姟涓庨獙璇佺郴缁熷紑鍙?md
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ST - 统计分析工具
模块代号: ST (Statistical Tools)
开发状态: ⏳ 规划中
商业价值: ⭐⭐⭐⭐ 高频
独立性: ⭐⭐⭐⭐
优先级: P2
📋 模块概述
统计分析工具提供100+种轻量化统计工具,满足即时、小型的分析需求。
🎯 核心功能
工具分类
描述性统计:
- 均值、中位数、标准差
- 频数分布
- 交叉表
推断性统计:
- t检验
- 卡方检验
- 方差分析(ANOVA)
相关与回归:
- 相关分析
- 线性回归
- Logistic回归
高级分析:
- ROC曲线
- 生存分析
- Meta分析
📂 文档结构
ST-统计分析工具/
├── [AI对接] ST快速上下文.md # ⏳ 待创建
├── 00-项目概述/
│ └── 02-工具清单(100+).md # ⏳ 待创建
└── README.md # ✅ 当前文档
🔗 依赖的通用能力
- 文档处理引擎 - 数据导入
🎯 商业模式
与SSA模块协同售卖
最后更新: 2025-11-06
维护人: 技术架构师