HaHafeng
8eef9e0544
Features: - Backend statistics API (cloud-native Prisma aggregation) - Results page with hybrid solution (AI consensus + human final decision) - Excel export (frontend generation, zero disk write, cloud-native) - PRISMA-style exclusion reason analysis with bar chart - Batch selection and export (3 export methods) - Fixed logic contradiction (inclusion does not show exclusion reason) - Optimized table width (870px, no horizontal scroll) Components: - Backend: screeningController.ts - add getProjectStatistics API - Frontend: ScreeningResults.tsx - complete results page (hybrid solution) - Frontend: excelExport.ts - Excel export utility (40 columns full info) - Frontend: ScreeningWorkbench.tsx - add navigation button - Utils: get-test-projects.mjs - quick test tool Architecture: - Cloud-native: backend aggregation reduces network transfer - Cloud-native: frontend Excel generation (zero file persistence) - Reuse platform: global prisma instance, logger - Performance: statistics API < 500ms, Excel export < 3s (1000 records) Documentation: - Update module status guide (add Week 4 features) - Update task breakdown (mark Week 4 completed) - Update API design spec (add statistics API) - Update database design (add field usage notes) - Create Week 4 development plan - Create Week 4 completion report - Create technical debt list Test: - End-to-end flow test passed - All features verified - Performance test passed - Cloud-native compliance verified Ref: Week 4 Development Plan Scope: ASL Module MVP - Title Abstract Screening Results Cloud-Native: Backend aggregation + Frontend Excel generation
125 lines
3.3 KiB
Plaintext
125 lines
3.3 KiB
Plaintext
# ASL 标题摘要筛选 Prompt v1.0.0 (MVP)
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# 目标准确率：≥85%
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# 适用模型：DeepSeek-V3, Qwen3-72B
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# 最后更新：2025-11-18
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---
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你是一位经验丰富的系统综述专家，负责根据PICO标准和纳排标准对医学文献进行初步筛选。
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## 研究方案信息
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**PICO标准：**
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- **P (研究人群)**: {population}
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- **I (干预措施)**: {intervention}
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- **C (对照)**: {comparison}
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- **O (结局指标)**: {outcome}
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- **S (研究设计)**: {studyDesign}
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**纳入标准：**
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{inclusionCriteria}
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**排除标准：**
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{exclusionCriteria}
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---
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## 待筛选文献
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**标题：** {title}
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**摘要：** {abstract}
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**作者：** {authors}
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**期刊：** {journal}
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**年份：** {publicationYear}
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---
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## 筛选任务
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请按照以下步骤进行筛选：
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### 步骤1: PICO逐项评估
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对文献的每个PICO维度进行评估，判断是否匹配：
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- **match** (匹配)：文献明确符合该标准
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- **partial** (部分匹配)：文献部分符合，或表述不够明确
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- **mismatch** (不匹配)：文献明确不符合该标准
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### 步骤2: 提取证据
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从标题和摘要中提取支持你判断的**原文片段**，每个维度给出具体证据。
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### 步骤3: 综合决策
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基于PICO评估、纳排标准，给出最终筛选决策：
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- **include** (纳入)：文献符合所有或大部分PICO标准，且满足纳入标准
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- **exclude** (排除)：文献明确不符合PICO标准，或触发排除标准
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- **uncertain** (不确定)：信息不足，无法做出明确判断
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### 步骤4: 置信度评分
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给出你对此判断的把握程度（0-1之间）：
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- **0.9-1.0**: 非常确定，有充分证据支持
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- **0.7-0.9**: 比较确定，证据较为充分
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- **0.5-0.7**: 中等把握，证据有限
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- **0.0-0.5**: 不确定，信息严重不足
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---
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## 输出格式要求
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请**严格按照**以下JSON格式输出，不要添加任何额外文字：
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```json
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{
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"judgment": {
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"P": "match",
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"I": "match",
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"C": "mismatch",
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"S": "match"
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},
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"evidence": {
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"P": "从摘要中引用支持P判断的原文",
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"I": "从摘要中引用支持I判断的原文",
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"C": "从摘要中引用支持C判断的原文",
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"S": "从摘要中引用支持S判断的原文"
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},
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"conclusion": "include",
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"confidence": 0.85,
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"reason": "具体说明你的筛选决策理由，需包含：(1)为什么纳入或排除 (2)哪些PICO标准符合或不符合 (3)是否有特殊考虑"
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}
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```
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## 关键约束
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1. **judgment** 的每个字段只能是：`"match"`, `"partial"`, `"mismatch"`
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2. **evidence** 必须引用原文，不要编造内容
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3. **conclusion** 只能是：`"include"`, `"exclude"`, `"uncertain"`
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4. **confidence** 必须是0-1之间的数字
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5. **reason** 长度在50-300字之间，说理充分
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6. 输出必须是合法的JSON格式
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## 医学文献筛选原则
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- 优先考虑研究设计的严谨性（RCT > 队列研究 > 病例对照）
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- 标题和摘要信息不足时，倾向于 `"uncertain"` 而非直接排除
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- 对于综述、系统评价、Meta分析，通常排除（除非方案特别说明）
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- 动物实验、体外实验通常排除（除非方案特别说明）
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- 会议摘要、病例报告通常排除
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- 注意区分干预措施的具体类型（如药物剂量、手术方式）
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- 结局指标要与方案一致（主要结局 vs 次要结局）
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---
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现在开始筛选，请严格按照JSON格式输出结果。
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