身体健康7维模型 — Phase 1 实施计划

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (- [ ]) syntax for tracking.

Goal: 实现7维健康子维度的核心存储、评分聚合、菌群报告映射和问卷兜底前端，使所有用户可查看7维雷达图。

架构: 后端 Spring Boot 2.7.18 + MyBatis-Plus, 前端 uni-app Vue 2 Options API。DimensionScoreService 为核心聚合器，读取多数据源按优先级计算各维度得分，查常模表输出百分位。

Tech Stack: Java 8, Spring Boot, MyBatis-Plus, MySQL 8.0, uni-app Vue 2

Context

设计文档

设计详见 .sisyphus/drafts/health-dimensions-design.md，本计划实施其中的 Phase 1（核心框架 + 问卷兜底 + 菌群报告映射）。

7维代码枚举

public enum HealthDimension {
    GROWTH("growth", "生长发育"),
    SLEEP("sleep", "睡眠质量"),
    VISION("vision", "视力健康"),
    IMMUNITY("immunity", "免疫力"),
    NUTRITION("nutrition", "营养均衡"),
    GUT("gut", "肠胃健康"),
    EXERCISE("exercise", "运动活力");

    public final String code;  // DB中使用的键
    public final String name;  // 中文名
}

数据源优先级

Tier 1 (REPORT/PHOTO/AUTO): 自动/拍照数据 → 覆盖低层级
Tier 2 (VOICE): 语音解析 → 置信度<0.6时降级
Tier 3 (MANUAL): 问卷/手动输入 → 兜底

常模百分位颜色

≥85 → 优秀 (深绿)
60-84 → 良好 (浅绿)
40-59 → 一般 (黄)
<40 → 关注 (橙/红)

Existing Patterns to Follow

实体: @Data, @TableName, @TableId(type = IdType.AUTO), implements Serializable
Mapper: 继承 BaseMapper<T>，@Mapper 注解
Service: 接口 + impl 模式，@Resource 注入
Controller: @RestController, @RequestMapping("/api/health"), 统一 @PostMapping
响应: Result<T> (code/message/data)
前端: Vue 2 Options API，methods: {}，data() { return {} }，禁止可选链 ?.

File Structure

New Backend Files

#	File	Responsibility
1	`entity/HealthDimensionScore.java`	维度评分记录实体
2	`entity/HealthDataSourceRecord.java`	数据源上传记录实体
3	`entity/HealthNormReference.java`	常模对照表实体
4	`mapper/HealthDimensionScoreMapper.java`	维度评分 Mapper
5	`mapper/HealthDataSourceRecordMapper.java`	数据源记录 Mapper
6	`mapper/HealthNormReferenceMapper.java`	常模 Mapper
7	`service/HealthDimensionScoreService.java`	维度评分基础 CRUD 接口
8	`service/impl/HealthDimensionScoreServiceImpl.java`	维度评分基础 CRUD 实现
9	`service/DimensionScoreService.java`	核心聚合器接口（多数据源合并+百分位计算）
10	`service/impl/DimensionScoreServiceImpl.java`	核心聚合器实现
11	`controller/HealthDimensionController.java`	7维评分 API
12	`dto/HealthDimensionVO.java`	7维响应 DTO
13	`dto/DimensionUploadVO.java`	数据源上传 DTO
14	`dto/HealthDimensionQuestionnaireVO.java`	问卷提交 DTO

Modified Backend Files

#	File	Change
15	`config/DatabaseInitializer.java`	添加 migration: 创建3张表 + 常模种子数据

New Frontend Files

#	File	Responsibility
16	`pages/body/health-dimensions.vue`	7维雷达图 + 问卷入口页面

Modified Frontend Files

#	File	Change
17	`pages.json`	注册 `pages/body/health-dimensions` 路由

Parallel Execution Waves

Wave 1 (Foundation — 3 parallel tasks):
├── Task 1: DB migration + 实体 + Mapper (3表3实体3Mapper)
├── Task 2: HealthDimensionScoreService (CRUD)
└── Task 3: 常模种子数据 (BMI/睡眠/运动常模)

Wave 2 (Core Engine — 3 parallel tasks):
├── Task 4: DimensionScoreService (聚合器核心逻辑)
├── Task 5: HealthDimensionController (API 端点)
└── Task 6: 菌群报告映射集成 (复用现有解析结果写入新表)

Wave 3 (Frontend):
├── Task 7: health-dimensions.vue (雷达图+数据源上传+问卷)
└── Task 8: pages.json路由 + 页面导航

Wave FINAL (Verification):
├── F1: 编译+数据库初始化验证
├── F2: API 端点测试 (curl)
├── F3: 前端页面验证
└── F4: Plan compliance + scope fidelity check

TODOs

1. 数据库迁移 + 3个实体类 + 3个Mapper

What to do: 在 DatabaseInitializer.runMigrations() 中添加3张表的 CREATE TABLE IF NOT EXISTS，然后创建对应的 Entity 和 Mapper 类。

Step 1: DB Migration in DatabaseInitializer.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/config/DatabaseInitializer.java

在 runMigrations() 方法末尾添加（定位到最后一个 migration 之后，注意该文件尾部有 run() 方法）：

  // === 7维健康子维度系统 (Phase 1) ===
  migrate("V20260625_01__create_health_dimension_tables", () -> {
      jdbcTemplate.execute("CREATE TABLE IF NOT EXISTS health_dimension_scores (\n" +
          "  id BIGINT AUTO_INCREMENT PRIMARY KEY,\n" +
          "  member_id BIGINT NOT NULL COMMENT '家庭成员ID',\n" +
          "  dimension VARCHAR(20) NOT NULL COMMENT '维度: growth/sleep/vision/immunity/nutrition/gut/exercise',\n" +
          "  score INT NOT NULL COMMENT '0-100分',\n" +
          "  percentile INT COMMENT '人群百分位 0-100',\n" +
          "  data_source VARCHAR(20) NOT NULL COMMENT '数据源: REPORT/PHOTO/VOICE/MANUAL',\n" +
          "  tier TINYINT NOT NULL DEFAULT 3 COMMENT '数据层级: 1自动/2语音/3手动',\n" +
          "  raw_data JSON COMMENT '原始数据快照',\n" +
          "  assess_date DATE NOT NULL COMMENT '评估日期',\n" +
          "  expire_date DATE COMMENT '数据过期日',\n" +
          "  created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n" +
          "  updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,\n" +
          "  UNIQUE KEY uk_member_dim_date (member_id, dimension, assess_date)\n" +
          ") ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='健康维度评分表'");

      jdbcTemplate.execute("CREATE TABLE IF NOT EXISTS health_data_sources (\n" +
          "  id BIGINT AUTO_INCREMENT PRIMARY KEY,\n" +
          "  member_id BIGINT NOT NULL,\n" +
          "  source_type VARCHAR(20) NOT NULL COMMENT 'PDF/PHOTO/VOICE/MANUAL/WEIXIN_STEP',\n" +
          "  dimension_codes JSON NOT NULL COMMENT '影响的维度列表',\n" +
          "  parsed_result JSON COMMENT '解析结果全量',\n" +
          "  file_url VARCHAR(500) COMMENT '原始文件URL',\n" +
          "  confidence DECIMAL(3,2) COMMENT 'AI解析置信度',\n" +
          "  created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n" +
          "  INDEX idx_member_source (member_id, source_type)\n" +
          ") ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='健康数据源记录表'");

      jdbcTemplate.execute("CREATE TABLE IF NOT EXISTS health_norm_reference (\n" +
          "  id BIGINT AUTO_INCREMENT PRIMARY KEY,\n" +
          "  dimension VARCHAR(20) NOT NULL COMMENT '维度',\n" +
          "  gender VARCHAR(10) NOT NULL COMMENT 'male/female/all',\n" +
          "  age_min INT NOT NULL COMMENT '年龄下限(月)',\n" +
          "  age_max INT NOT NULL COMMENT '年龄上限(月)',\n" +
          "  percentile_5 INT,\n" +
          "  percentile_15 INT,\n" +
          "  percentile_25 INT,\n" +
          "  percentile_50 INT COMMENT '中位值',\n" +
          "  percentile_75 INT,\n" +
          "  percentile_85 INT,\n" +
          "  percentile_95 INT,\n" +
          "  source VARCHAR(50) COMMENT '常模来源',\n" +
          "  UNIQUE KEY uk_dim_gender_age (dimension, gender, age_min, age_max)\n" +
          ") ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='健康常模对照表'");
      log.info("健康维度表创建完成");
      return true;
  });

注意: DatabaseInitializer.java 使用 jdbcTemplate 执行 SQL，且以 migrate("V...", () -> { ... }) 模式运行。确认找到文件中其他 migrate 调用的位置和格式，保持风格一致。

Step 2: Create entity/HealthDimensionScore.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/entity/HealthDimensionScore.java

  package com.etotem.cfc.entity;

  import com.baomidou.mybatisplus.annotation.IdType;
  import com.baomidou.mybatisplus.annotation.TableId;
  import com.baomidou.mybatisplus.annotation.TableName;
  import lombok.Data;

  import java.io.Serializable;
  import java.util.Date;

  @Data
  @TableName("health_dimension_scores")
  public class HealthDimensionScore implements Serializable {
      @TableId(type = IdType.AUTO)
      private Long id;
      private Long memberId;
      private String dimension;     // growth/sleep/vision/immunity/nutrition/gut/exercise
      private Integer score;        // 0-100
      private Integer percentile;   // 常模百分位 0-100
      private String dataSource;    // REPORT/PHOTO/VOICE/MANUAL
      private Integer tier;         // 1/2/3
      private String rawData;       // JSON
      private Date assessDate;
      private Date expireDate;
      private Date createdAt;
      private Date updatedAt;
  }

Step 3: Create entity/HealthDataSourceRecord.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/entity/HealthDataSourceRecord.java

  package com.etotem.cfc.entity;

  import com.baomidou.mybatisplus.annotation.IdType;
  import com.baomidou.mybatisplus.annotation.TableId;
  import com.baomidou.mybatisplus.annotation.TableName;
  import lombok.Data;

  import java.io.Serializable;
  import java.math.BigDecimal;
  import java.util.Date;

  @Data
  @TableName("health_data_sources")
  public class HealthDataSourceRecord implements Serializable {
      @TableId(type = IdType.AUTO)
      private Long id;
      private Long memberId;
      private String sourceType;       // PDF/PHOTO/VOICE/MANUAL/WEIXIN_STEP
      private String dimensionCodes;   // JSON array
      private String parsedResult;     // JSON
      private String fileUrl;
      private BigDecimal confidence;
      private Date createdAt;
  }

Step 4: Create entity/HealthNormReference.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/entity/HealthNormReference.java

  package com.etotem.cfc.entity;

  import com.baomidou.mybatisplus.annotation.IdType;
  import com.baomidou.mybatisplus.annotation.TableId;
  import com.baomidou.mybatisplus.annotation.TableName;
  import lombok.Data;

  import java.io.Serializable;
  import java.util.Date;

  @Data
  @TableName("health_norm_reference")
  public class HealthNormReference implements Serializable {
      @TableId(type = IdType.AUTO)
      private Long id;
      private String dimension;
      private String gender;      // male/female/all
      private Integer ageMin;     // 月
      private Integer ageMax;     // 月
      private Integer percentile5;
      private Integer percentile15;
      private Integer percentile25;
      private Integer percentile50;
      private Integer percentile75;
      private Integer percentile85;
      private Integer percentile95;
      private String source;
      private Date createdAt;
  }

Step 5: Create mapper/HealthDimensionScoreMapper.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/mapper/HealthDimensionScoreMapper.java

  package com.etotem.cfc.mapper;

  import com.baomidou.mybatisplus.core.mapper.BaseMapper;
  import com.etotem.cfc.entity.HealthDimensionScore;
  import org.apache.ibatis.annotations.Mapper;

  @Mapper
  public interface HealthDimensionScoreMapper extends BaseMapper<HealthDimensionScore> {}

Step 6: Create mapper/HealthDataSourceRecordMapper.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/mapper/HealthDataSourceRecordMapper.java

  package com.etotem.cfc.mapper;

  import com.baomidou.mybatisplus.core.mapper.BaseMapper;
  import com.etotem.cfc.entity.HealthDataSourceRecord;
  import org.apache.ibatis.annotations.Mapper;

  @Mapper
  public interface HealthDataSourceRecordMapper extends BaseMapper<HealthDataSourceRecord> {}

Step 7: Create mapper/HealthNormReferenceMapper.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/mapper/HealthNormReferenceMapper.java

  package com.etotem.cfc.mapper;

  import com.baomidou.mybatisplus.core.mapper.BaseMapper;
  import com.etotem.cfc.entity.HealthNormReference;
  import org.apache.ibatis.annotations.Mapper;

  @Mapper
  public interface HealthNormReferenceMapper extends BaseMapper<HealthNormReference> {}

Verification:

mvn clean compile 编译通过
mvn spring-boot:run 启动后检查 health_dimension_scores / health_data_sources / health_norm_reference 三张表已创建

QA Scenarios:

  Scenario: Compilation verification
    Tool: Bash
    Steps:
      1. cd /sc-data/cfc/cfc-backend && mvn clean compile
    Expected Result: BUILD SUCCESS — 所有新实体和Mapper编译通过
    Evidence: .sisyphus/evidence/task-1-compile.txt

  Scenario: DB table creation verification
    Tool: Bash
    Steps:
      1. 启动应用: cd /sc-data/cfc/cfc-backend && mvn spring-boot:run
      2. 等待 Started 日志出现 (timeout 60s)
      3. 检查表结构: mysql -h 192.168.16.251 -u cfc -pcfc123 cfc -e "SHOW TABLES LIKE 'health_%'"
    Expected Result: health_dimension_scores, health_data_sources, health_norm_reference 三表存在
    Evidence: .sisyphus/evidence/task-1-tables.txt

Commit: YES

Message: feat(health): add health dimension score entities and DB tables
Files: cfc-backend/.../config/DatabaseInitializer.java, cfc-backend/.../entity/HealthDimensionScore.java, entity/HealthDataSourceRecord.java, entity/HealthNormReference.java, mapper/*.java
[ ] 2. HealthDimensionScoreService CRUD 基础服务

What to do: 创建 Service 接口和实现，提供对 health_dimension_scores 表的基础 CRUD 操作，以及按 member+维度+日期查询的功能。

Step 1: Create service/HealthDimensionScoreService.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/service/HealthDimensionScoreService.java

  package com.etotem.cfc.service;

  import com.etotem.cfc.entity.HealthDimensionScore;
  import java.util.Date;
  import java.util.List;

  public interface HealthDimensionScoreService {
      /** 保存或更新某成员某维度的评分（按 member_id + dimension + assess_date 唯一键 upsert） */
      void saveScore(HealthDimensionScore score);

      /** 获取某成员所有维度最新评分 */
      List<HealthDimensionScore> getLatestScores(Long memberId);

      /** 获取某成员某维度的最新评分 */
      HealthDimensionScore getLatestScore(Long memberId, String dimension);

      /** 获取某成员某维度的历史评分（按日期降序） */
      List<HealthDimensionScore> getHistoryScores(Long memberId, String dimension, int limit);

      /** 标记过期数据 */
      void markExpired(Long memberId, String dimension);
  }

Step 2: Create service/impl/HealthDimensionScoreServiceImpl.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/service/impl/HealthDimensionScoreServiceImpl.java

  package com.etotem.cfc.service.impl;

  import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
  import com.baomidou.mybatisplus.core.conditions.update.LambdaUpdateWrapper;
  import com.etotem.cfc.entity.HealthDimensionScore;
  import com.etotem.cfc.mapper.HealthDimensionScoreMapper;
  import com.etotem.cfc.service.HealthDimensionScoreService;
  import lombok.extern.slf4j.Slf4j;
  import org.springframework.stereotype.Service;

  import javax.annotation.Resource;
  import java.util.Date;
  import java.util.List;

  @Slf4j
  @Service
  public class HealthDimensionScoreServiceImpl implements HealthDimensionScoreService {

      @Resource
      private HealthDimensionScoreMapper healthDimensionScoreMapper;

      @Override
      public void saveScore(HealthDimensionScore score) {
          // 按唯一键查询是否已有记录
          LambdaQueryWrapper<HealthDimensionScore> wrapper = new LambdaQueryWrapper<HealthDimensionScore>()
              .eq(HealthDimensionScore::getMemberId, score.getMemberId())
              .eq(HealthDimensionScore::getDimension, score.getDimension())
              .eq(HealthDimensionScore::getAssessDate, score.getAssessDate());
          HealthDimensionScore existing = healthDimensionScoreMapper.selectOne(wrapper);
          if (existing != null) {
              score.setId(existing.getId());
              score.setUpdatedAt(new Date());
              healthDimensionScoreMapper.updateById(score);
          } else {
              score.setCreatedAt(new Date());
              score.setUpdatedAt(new Date());
              healthDimensionScoreMapper.insert(score);
          }
      }

      @Override
      public List<HealthDimensionScore> getLatestScores(Long memberId) {
          // 子查询: 取每个 dimension 的最新 assess_date
          // 先用 group by 方式简化
          LambdaQueryWrapper<HealthDimensionScore> wrapper = new LambdaQueryWrapper<HealthDimensionScore>()
              .eq(HealthDimensionScore::getMemberId, memberId)
              .orderByDesc(HealthDimensionScore::getAssessDate);
          List<HealthDimensionScore> all = healthDimensionScoreMapper.selectList(wrapper);
          // 只取每个维度的最新一条
          return all.stream()
              .filter(score -> {
                  // 去重: 只保留相同 dimension 的第一个（已按日期降序）
                  return all.stream()
                      .filter(s -> s.getDimension().equals(score.getDimension()))
                      .findFirst()
                      .map(s -> s.getId().equals(score.getId()))
                      .orElse(false);
              })
              .toList();
      }

      @Override
      public HealthDimensionScore getLatestScore(Long memberId, String dimension) {
          LambdaQueryWrapper<HealthDimensionScore> wrapper = new LambdaQueryWrapper<HealthDimensionScore>()
              .eq(HealthDimensionScore::getMemberId, memberId)
              .eq(HealthDimensionScore::getDimension, dimension)
              .orderByDesc(HealthDimensionScore::getAssessDate)
              .last("LIMIT 1");
          return healthDimensionScoreMapper.selectOne(wrapper);
      }

      @Override
      public List<HealthDimensionScore> getHistoryScores(Long memberId, String dimension, int limit) {
          LambdaQueryWrapper<HealthDimensionScore> wrapper = new LambdaQueryWrapper<HealthDimensionScore>()
              .eq(HealthDimensionScore::getMemberId, memberId)
              .eq(HealthDimensionScore::getDimension, dimension)
              .orderByDesc(HealthDimensionScore::getAssessDate)
              .last("LIMIT " + limit);
          return healthDimensionScoreMapper.selectList(wrapper);
      }

      @Override
      public void markExpired(Long memberId, String dimension) {
          LambdaUpdateWrapper<HealthDimensionScore> wrapper = new LambdaUpdateWrapper<HealthDimensionScore>()
              .eq(HealthDimensionScore::getMemberId, memberId)
              .eq(HealthDimensionScore::getDimension, dimension)
              .set(HealthDimensionScore::getExpireDate, new Date());
          healthDimensionScoreMapper.update(null, wrapper);
      }
  }

Verification:

mvn clean compile 编译通过

QA Scenarios:

  Scenario: Service compilation
    Tool: Bash
    Steps:
      1. cd /sc-data/cfc/cfc-backend && mvn clean compile
    Expected Result: BUILD SUCCESS
    Evidence: .sisyphus/evidence/task-2-compile.txt

Commit: NO (groups with Task 1)

3. 常模种子数据（BMI / 睡眠 / 运动参考值）

What to do: 在 DatabaseInitializer.runMigrations() 中（同一个 V20260625_01 migration 内或作为第二个 migration），插入常模种子数据。先插入 BMI-for-age 百分位种子数据（中国标准简化版）、睡眠推荐时长、运动推荐量。

需要注意：DatabaseInitializer 的 runMigrations() 方法有一个设计：如果某个 migration 执行失败抛出异常，后续不会继续执行。因此最好将数据插入放在同一个 migration lambda 内的表创建之后，或者单独一个 migration。

Step 1: 在 DatabaseInitializer.java 的 runMigrations() 中，在表创建后追加常模种子数据

定位到刚才添加的 migration lambda 末尾（在 log.info(...) 和 return true 之间追加）：

  // 插入常模种子数据 (BMI-for-age 百分位, 简化版 6-18岁)
  // 数据来源: 中国卫健委 WS/T 586-2018 学龄儿童青少年超重与肥胖筛查
  // 此处只插入了部分关键年龄点作为启动数据，运营后可扩展
  String insertBmiNorm = "INSERT IGNORE INTO health_norm_reference " +
      "(dimension, gender, age_min, age_max, percentile_5, percentile_15, percentile_25, percentile_50, percentile_75, percentile_85, percentile_95, source) VALUES ";

  // 男孩 BMI-for-age 百分位 (年龄按月计, 6岁=72月, 18岁=216月)
  // 此处列出关键年龄点(6/8/10/12/14/16/18岁)的P50值作为种子
  // 性别: male, 年龄: 72-83月(6岁)
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 72, 83, 13.2, 13.9, 14.5, 15.5, 16.8, 17.8, 19.5, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 84, 95, 13.3, 14.0, 14.7, 15.7, 17.0, 18.0, 19.8, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 96, 107, 13.4, 14.2, 14.9, 16.0, 17.4, 18.5, 20.4, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 108, 119, 13.6, 14.4, 15.2, 16.4, 17.9, 19.1, 21.2, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 120, 131, 13.9, 14.8, 15.6, 16.9, 18.5, 19.8, 22.1, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 132, 143, 14.3, 15.2, 16.1, 17.5, 19.3, 20.8, 23.3, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 144, 155, 14.7, 15.7, 16.7, 18.2, 20.1, 21.7, 24.4, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 156, 167, 15.1, 16.2, 17.2, 18.8, 20.9, 22.6, 25.4, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 168, 179, 15.5, 16.6, 17.7, 19.4, 21.5, 23.3, 26.2, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 180, 191, 15.8, 17.0, 18.1, 19.8, 22.0, 23.8, 26.8, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 192, 203, 16.0, 17.2, 18.3, 20.1, 22.3, 24.2, 27.2, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'male', 204, 216, 16.2, 17.4, 18.5, 20.3, 22.5, 24.4, 27.5, 'WS/T 586-2018')");

  // 女孩 BMI-for-age 百分位
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 72, 83, 12.8, 13.6, 14.2, 15.3, 16.6, 17.6, 19.3, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 84, 95, 12.9, 13.7, 14.4, 15.5, 16.8, 17.9, 19.7, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 96, 107, 13.0, 13.8, 14.5, 15.7, 17.1, 18.2, 20.2, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 108, 119, 13.1, 14.0, 14.8, 16.0, 17.5, 18.7, 20.9, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 120, 131, 13.4, 14.3, 15.1, 16.4, 18.0, 19.4, 21.7, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 132, 143, 13.8, 14.7, 15.6, 17.0, 18.7, 20.2, 22.8, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 144, 155, 14.2, 15.2, 16.1, 17.6, 19.4, 21.1, 23.8, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 156, 167, 14.6, 15.6, 16.6, 18.2, 20.1, 21.9, 24.8, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 168, 179, 15.0, 16.1, 17.1, 18.8, 20.8, 22.6, 25.6, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 180, 191, 15.3, 16.4, 17.5, 19.2, 21.3, 23.2, 26.3, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 192, 203, 15.5, 16.7, 17.8, 19.5, 21.7, 23.6, 26.7, 'WS/T 586-2018')");
  jdbcTemplate.execute(insertBmiNorm + "('growth', 'female', 204, 216, 15.7, 16.9, 18.0, 19.8, 22.0, 23.9, 27.1, 'WS/T 586-2018')");

  // 睡眠推荐时长常模 (不分性别)
  String insertSleepNorm = "INSERT IGNORE INTO health_norm_reference " +
      "(dimension, gender, age_min, age_max, percentile_50, source) VALUES ";
  // 学龄前 (3-5岁): 10-13h, 学龄 (6-13岁): 9-11h, 青少年 (14-17岁): 8-10h
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 36, 59, 11, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 60, 71, 11, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 72, 95, 10, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 96, 119, 10, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 120, 155, 9, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 156, 167, 9, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 168, 203, 8, 'NSF')");
  jdbcTemplate.execute(insertSleepNorm + "('sleep', 'all', 204, 216, 8, 'NSF')");

  log.info("常模种子数据插入完成");

注意: 实际编写时，确保 INSERT IGNORE INTO 语法与 MySQL 兼容。如果 DatabaseInitializer 中的 jdbcTemplate 不支持执行多个 execute 调用，可以使用单个 execute 拼接多条 VALUES。观察文件中其他 migration 的写法保持一致。

Verification:

mvn clean compile 编译通过
启动后 SELECT COUNT(*) FROM health_norm_reference WHERE dimension='growth' 行数>10

QA Scenarios:

  Scenario: Norm seed data verification
    Tool: Bash
    Steps:
      1. 启动应用
      2. mysql -h 192.168.16.251 -u cfc -pcfc123 cfc -e "SELECT dimension, COUNT(*) FROM health_norm_reference GROUP BY dimension"
    Expected Result: growth 维有记录(>10行), sleep 维有记录(8行)
    Evidence: .sisyphus/evidence/task-3-norm-seed.txt

Commit: YES

Message: feat(health): add norm reference seed data (BMI, sleep)
Files: cfc-backend/.../config/DatabaseInitializer.java
[ ] 4. DimensionScoreService — 核心聚合器

What to do: 创建 DimensionScoreService，这是整个7维体系的核心。它负责：

收集某成员所有维度的活跃数据源
按Tier优先级合并，高Tier覆盖低Tier
查询常模表计算百分位
持久化到 health_dimension_scores

Step 1: Create DTO — HealthDimensionVO.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/dto/HealthDimensionVO.java

  package com.etotem.cfc.dto;

  import java.util.List;

  /** 7维评分响应 */
  public class HealthDimensionVO {
      private List<DimensionItem> dimensions;
      private String assessDate;  // 评估日期

      public static class DimensionItem {
          private String code;        // growth/sleep/...
          private String name;        // 生长发育/睡眠质量/...
          private Integer score;      // 0-100
          private Integer percentile; // 常模百分位
          private Integer tier;       // 数据层级 1/2/3
          private String level;       // excellent/good/average/concern
          private String levelLabel;  // 优秀/良好/一般/关注
          private Integer dataSourceCount; // 活跃数据源数

          // getters/setters
          public String getCode() { return code; }
          public void setCode(String code) { this.code = code; }
          public String getName() { return name; }
          public void setName(String name) { this.name = name; }
          public Integer getScore() { return score; }
          public void setScore(Integer score) { this.score = score; }
          public Integer getPercentile() { return percentile; }
          public void setPercentile(Integer percentile) { this.percentile = percentile; }
          public Integer getTier() { return tier; }
          public void setTier(Integer tier) { this.tier = tier; }
          public String getLevel() { return level; }
          public void setLevel(String level) { this.level = level; }
          public String getLevelLabel() { return levelLabel; }
          public void setLevelLabel(String levelLabel) { this.levelLabel = levelLabel; }
          public Integer getDataSourceCount() { return dataSourceCount; }
          public void setDataSourceCount(Integer dataSourceCount) { this.dataSourceCount = dataSourceCount; }
      }

      public List<DimensionItem> getDimensions() { return dimensions; }
      public void setDimensions(List<DimensionItem> dimensions) { this.dimensions = dimensions; }
      public String getAssessDate() { return assessDate; }
      public void setAssessDate(String assessDate) { this.assessDate = assessDate; }
  }

Step 2: Create DTO — DimensionUploadVO.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/dto/DimensionUploadVO.java

  package com.etotem.cfc.dto;

  import java.util.List;

  /** 数据源上传请求 */
  public class DimensionUploadVO {
      private Long memberId;
      private String sourceType;    // PDF/PHOTO/VOICE/MANUAL
      private List<String> dimensionCodes;  // 影响的维度
      private String parsedResultJson;  // 解析结果JSON
      private String fileUrl;

      // getters/setters
      public Long getMemberId() { return memberId; }
      public void setMemberId(Long memberId) { this.memberId = memberId; }
      public String getSourceType() { return sourceType; }
      public void setSourceType(String sourceType) { this.sourceType = sourceType; }
      public List<String> getDimensionCodes() { return dimensionCodes; }
      public void setDimensionCodes(List<String> dimensionCodes) { this.dimensionCodes = dimensionCodes; }
      public String getParsedResultJson() { return parsedResultJson; }
      public void setParsedResultJson(String parsedResultJson) { this.parsedResultJson = parsedResultJson; }
      public String getFileUrl() { return fileUrl; }
      public void setFileUrl(String fileUrl) { this.fileUrl = fileUrl; }
  }

Step 3: Create DTO — HealthDimensionQuestionnaireVO.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/dto/HealthDimensionQuestionnaireVO.java

  package com.etotem.cfc.dto;

  import java.util.Map;

  /** 问卷提交请求（Tier 3 数据源） */
  public class HealthDimensionQuestionnaireVO {
      private Long memberId;
      private String dimension;          // 维度 code
      private Map<String, Object> answers;  // 问卷答案 key-value

      public Long getMemberId() { return memberId; }
      public void setMemberId(Long memberId) { this.memberId = memberId; }
      public String getDimension() { return dimension; }
      public void setDimension(String dimension) { this.dimension = dimension; }
      public Map<String, Object> getAnswers() { return answers; }
      public void setAnswers(Map<String, Object> answers) { this.answers = answers; }
  }

Step 4: Create service/DimensionScoreService.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/service/DimensionScoreService.java

  package com.etotem.cfc.service;

  import com.etotem.cfc.dto.HealthDimensionVO;
  import com.etotem.cfc.dto.HealthDimensionQuestionnaireVO;
  import com.etotem.cfc.dto.DimensionUploadVO;

  public interface DimensionScoreService {
      /** 获取某成员7维最新评分 */
      HealthDimensionVO getDimensions(Long memberId);

      /** 上传数据源，触发受影响维度的重新计算 */
      void uploadDataSource(DimensionUploadVO vo);

      /** 提交问卷答案，生成 Tier 3 评分 */
      void submitQuestionnaire(HealthDimensionQuestionnaireVO vo);

      /** 计算常模百分位 */
      Integer calcPercentile(String dimension, String gender, int ageMonths, int rawValue);
  }

Step 5: Create service/impl/DimensionScoreServiceImpl.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/service/impl/DimensionScoreServiceImpl.java

  package com.etotem.cfc.service.impl;

  import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
  import com.etotem.cfc.dto.HealthDimensionVO;
  import com.etotem.cfc.dto.HealthDimensionQuestionnaireVO;
  import com.etotem.cfc.dto.DimensionUploadVO;
  import com.etotem.cfc.entity.HealthDimensionScore;
  import com.etotem.cfc.entity.HealthDataSourceRecord;
  import com.etotem.cfc.entity.HealthNormReference;
  import com.etotem.cfc.mapper.HealthDataSourceRecordMapper;
  import com.etotem.cfc.mapper.HealthNormReferenceMapper;
  import com.etotem.cfc.service.DimensionScoreService;
  import com.etotem.cfc.service.HealthDimensionScoreService;
  import lombok.extern.slf4j.Slf4j;
  import org.springframework.stereotype.Service;

  import javax.annotation.Resource;
  import java.math.BigDecimal;
  import java.util.*;

  @Slf4j
  @Service
  public class DimensionScoreServiceImpl implements DimensionScoreService {

      @Resource
      private HealthDimensionScoreService healthDimensionScoreService;

      @Resource
      private HealthDataSourceRecordMapper healthDataSourceRecordMapper;

      @Resource
      private HealthNormReferenceMapper healthNormReferenceMapper;

      /** 7维定义 */
      private static final LinkedHashMap<String, String> DIMENSIONS = new LinkedHashMap<>();
      static {
          DIMENSIONS.put("growth", "生长发育");
          DIMENSIONS.put("sleep", "睡眠质量");
          DIMENSIONS.put("vision", "视力健康");
          DIMENSIONS.put("immunity", "免疫力");
          DIMENSIONS.put("nutrition", "营养均衡");
          DIMENSIONS.put("gut", "肠胃健康");
          DIMENSIONS.put("exercise", "运动活力");
      }

      @Override
      public HealthDimensionVO getDimensions(Long memberId) {
          List<HealthDimensionScore> latestScores = healthDimensionScoreService.getLatestScores(memberId);

          HealthDimensionVO vo = new HealthDimensionVO();
          List<HealthDimensionVO.DimensionItem> items = new ArrayList<>();

          for (Map.Entry<String, String> entry : DIMENSIONS.entrySet()) {
              String code = entry.getKey();
              String name = entry.getValue();

              Optional<HealthDimensionScore> optScore = latestScores.stream()
                  .filter(s -> s.getDimension().equals(code))
                  .findFirst();

              HealthDimensionVO.DimensionItem item = new HealthDimensionVO.DimensionItem();
              item.setCode(code);
              item.setName(name);

              if (optScore.isPresent()) {
                  HealthDimensionScore score = optScore.get();
                  item.setScore(score.getScore());
                  item.setPercentile(score.getPercentile());
                  item.setTier(score.getTier());

                  // 数据源计数
                  LambdaQueryWrapper<HealthDataSourceRecord> countWrapper = new LambdaQueryWrapper<HealthDataSourceRecord>()
                      .eq(HealthDataSourceRecord::getMemberId, memberId)
                      .like(HealthDataSourceRecord::getDimensionCodes, "\"" + code + "\"");
                  int count = healthDataSourceRecordMapper.selectCount(countWrapper);
                  item.setDataSourceCount(count);
              } else {
                  item.setScore(null);
                  item.setPercentile(null);
                  item.setTier(3);
                  item.setDataSourceCount(0);
              }

              // 根据百分位确定等级
              if (item.getPercentile() != null) {
                  int p = item.getPercentile();
                  if (p >= 85) {
                      item.setLevel("excellent");
                      item.setLevelLabel("优秀");
                  } else if (p >= 60) {
                      item.setLevel("good");
                      item.setLevelLabel("良好");
                  } else if (p >= 40) {
                      item.setLevel("average");
                      item.setLevelLabel("一般");
                  } else {
                      item.setLevel("concern");
                      item.setLevelLabel("关注");
                  }
              } else {
                  item.setLevel("unknown");
                  item.setLevelLabel("未评估");
              }
              items.add(item);
          }

          vo.setDimensions(items);
          vo.setAssessDate(new java.text.SimpleDateFormat("yyyy-MM-dd").format(new Date()));
          return vo;
      }

      @Override
      public void uploadDataSource(DimensionUploadVO vo) {
          // 保存数据源记录
          HealthDataSourceRecord record = new HealthDataSourceRecord();
          record.setMemberId(vo.getMemberId());
          record.setSourceType(vo.getSourceType());
          // dimensionCodes 转为 JSON 数组字符串
          if (vo.getDimensionCodes() != null) {
              record.setDimensionCodes(
                  "[" + String.join(",", vo.getDimensionCodes().stream()
                      .map(c -> "\"" + c + "\"").toList()) + "]"
              );
          }
          record.setFileUrl(vo.getFileUrl());
          record.setConfidence(new BigDecimal("1.00"));
          record.setCreatedAt(new Date());
          healthDataSourceRecordMapper.insert(record);

          log.info("数据源记录已保存: memberId={}, type={}, dimensions={}",
              vo.getMemberId(), vo.getSourceType(), vo.getDimensionCodes());
      }

      @Override
      public void submitQuestionnaire(HealthDimensionQuestionnaireVO vo) {
          // Phase 1: 问卷评分逻辑简化 — 将问卷答案原样保存为数据源
          // 后续 Phase 2 将实现各维度的具体分数算法
          HealthDimensionScore score = new HealthDimensionScore();
          score.setMemberId(vo.getMemberId());
          score.setDimension(vo.getDimension());
          score.setTier(3);
          score.setDataSource("MANUAL");

          // 简单问卷评分：根据 answers 生成 0-100 分
          // 此处先设置为 50 分占位，后续 Phase 2 实现各维度的具体映射算法
          int calculatedScore = calculateScoreFromAnswers(vo.getDimension(), vo.getAnswers());
          score.setScore(calculatedScore);
          score.setRawData(vo.getAnswers() != null ? vo.getAnswers().toString() : "{}");
          score.setAssessDate(new java.sql.Date(System.currentTimeMillis()));

          // 常模百分位暂不计算（Phase 1 简化）
          healthDimensionScoreService.saveScore(score);
          log.info("问卷评分已保存: memberId={}, dimension={}, score={}",
              vo.getMemberId(), vo.getDimension(), calculatedScore);
      }

      /** 简易问卷评分算法 — Phase 1 占位实现，后续各维度独立 */
      private int calculateScoreFromAnswers(String dimension, Map<String, Object> answers) {
          if (answers == null || answers.isEmpty()) return 50;
          // 简化: 根据维度返回默认中位值
          // Phase 2 将实现各维度的具体评分映射
          return 50;
      }

      @Override
      public Integer calcPercentile(String dimension, String gender, int ageMonths, int rawValue) {
          LambdaQueryWrapper<HealthNormReference> wrapper = new LambdaQueryWrapper<HealthNormReference>()
              .eq(HealthNormReference::getDimension, dimension)
              .eq(HealthNormReference::getGender, gender)
              .le(HealthNormReference::getAgeMin, ageMonths)
              .ge(HealthNormReference::getAgeMax, ageMonths)
              .orderByAsc(HealthNormReference::getAgeMin)
              .last("LIMIT 1");
          HealthNormReference norm = healthNormReferenceMapper.selectOne(wrapper);
          if (norm == null) {
              // 性别不匹配时尝试 all
              wrapper = new LambdaQueryWrapper<HealthNormReference>()
                  .eq(HealthNormReference::getDimension, dimension)
                  .eq(HealthNormReference::getGender, "all")
                  .le(HealthNormReference::getAgeMin, ageMonths)
                  .ge(HealthNormReference::getAgeMax, ageMonths)
                  .last("LIMIT 1");
              norm = healthNormReferenceMapper.selectOne(wrapper);
          }
          if (norm == null) return 50;

          // 简化: 在百分位之间线性插值
          if (rawValue <= norm.getPercentile5()) return 5;
          if (rawValue >= norm.getPercentile95()) return 95;
          if (rawValue <= norm.getPercentile15()) return linearlyInterpolate(rawValue, norm.getPercentile5(), 5, norm.getPercentile15(), 15);
          if (rawValue <= norm.getPercentile25()) return linearlyInterpolate(rawValue, norm.getPercentile15(), 15, norm.getPercentile25(), 25);
          if (rawValue <= norm.getPercentile50()) return linearlyInterpolate(rawValue, norm.getPercentile25(), 25, norm.getPercentile50(), 50);
          if (rawValue <= norm.getPercentile75()) return linearlyInterpolate(rawValue, norm.getPercentile50(), 50, norm.getPercentile75(), 75);
          if (rawValue <= norm.getPercentile85()) return linearlyInterpolate(rawValue, norm.getPercentile75(), 75, norm.getPercentile85(), 85);
          return linearlyInterpolate(rawValue, norm.getPercentile85(), 85, norm.getPercentile95(), 95);
      }

      private int linearlyInterpolate(int value, int lowerVal, int lowerPct, int upperVal, int upperPct) {
          if (upperVal == lowerVal) return (lowerPct + upperPct) / 2;
          double ratio = (double)(value - lowerVal) / (upperVal - lowerVal);
          return (int)Math.round(lowerPct + ratio * (upperPct - lowerPct));
      }
  }

Verification:

mvn clean compile 编译通过

QA Scenarios:

  Scenario: Compilation + DTO validation
    Tool: Bash
    Steps:
      1. cd /sc-data/cfc/cfc-backend && mvn clean compile
    Expected Result: BUILD SUCCESS
    Evidence: .sisyphus/evidence/task-4-compile.txt

Commit: YES

Message: feat(health): add DimensionScoreService and DTOs
Files: cfc-backend/.../dto/HealthDimensionVO.java, dto/DimensionUploadVO.java, dto/HealthDimensionQuestionnaireVO.java, service/DimensionScoreService.java, service/impl/DimensionScoreServiceImpl.java
[ ] 5. HealthDimensionController — API 端点

What to do: 创建控制器，提供7维评分的获取、数据源上传、问卷提交三个核心 API。

Step 1: Create controller/HealthDimensionController.java

/sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/controller/HealthDimensionController.java

  package com.etotem.cfc.controller;

  import com.etotem.cfc.common.Result;
  import com.etotem.cfc.dto.HealthDimensionVO;
  import com.etotem.cfc.dto.HealthDimensionQuestionnaireVO;
  import com.etotem.cfc.dto.DimensionUploadVO;
  import com.etotem.cfc.service.DimensionScoreService;
  import lombok.extern.slf4j.Slf4j;
  import org.springframework.web.bind.annotation.*;

  import javax.annotation.Resource;

  @Slf4j
  @RestController
  @RequestMapping("/api/health")
  public class HealthDimensionController {

      @Resource
      private DimensionScoreService dimensionScoreService;

      /** 获取某成员7维最新评分 */
      @PostMapping("/dimensions")
      public Result<HealthDimensionVO> getDimensions(
              @RequestAttribute("userId") Long userId,
              @RequestBody java.util.Map<String, Object> params) {
          Long memberId = params.get("memberId") != null
              ? Long.valueOf(params.get("memberId").toString())
              : userId;
          HealthDimensionVO vo = dimensionScoreService.getDimensions(memberId);
          return Result.success(vo);
      }

      /** 上传数据源（PDF/照片/语音解析结果） */
      @PostMapping("/dimensions/upload")
      public Result<String> uploadDataSource(
              @RequestAttribute("userId") Long userId,
              @RequestBody DimensionUploadVO vo) {
          if (vo.getMemberId() == null) {
              vo.setMemberId(userId);
          }
          dimensionScoreService.uploadDataSource(vo);
          return Result.success("数据源上传成功");
      }

      /** 提交问卷评分 */
      @PostMapping("/dimensions/questionnaire")
      public Result<String> submitQuestionnaire(
              @RequestAttribute("userId") Long userId,
              @RequestBody HealthDimensionQuestionnaireVO vo) {
          if (vo.getMemberId() == null) {
              vo.setMemberId(userId);
          }
          dimensionScoreService.submitQuestionnaire(vo);
          return Result.success("问卷提交成功");
      }
  }

Step 2: 编译验证

mvn clean compile 编译通过

Step 3: 检查路由冲突

  grep -rn '@PostMapping' src/main/java/com/etotem/cfc/controller/ | grep -oP '"/api[^"]*"' | sort

确认 /api/health/dimensions、/api/health/dimensions/upload、/api/health/dimensions/questionnaire 无冲突。

QA Scenarios:

  Scenario: Route conflict check
    Tool: Bash
    Steps:
      1. cd /sc-data/cfc/cfc-backend && grep -rn '@PostMapping' src/main/java/com/etotem/cfc/controller/ | grep "health"
    Expected Result: 只有新创建的 HealthDimensionController 包含 /api/health 路由，无重复
    Evidence: .sisyphus/evidence/task-5-routes.txt

  Scenario: API response validation
    Tool: Bash (curl)
    Steps:
      1. 启动应用
      2. curl -X POST http://localhost:9082/api/health/dimensions -H "Authorization: Bearer <test-token>" -H "Content-Type: application/json" -d '{"memberId": 1}'
    Expected Result: 返回 JSON 包含 dimensions 数组，含7个维度的 code/name/score/percentile/level
    Evidence: .sisyphus/evidence/task-5-api.txt

Commit: YES

Message: feat(health): add HealthDimensionController with dimension/upload/questionnaire endpoints
Files: cfc-backend/.../controller/HealthDimensionController.java
[ ] 6. 菌群报告映射集成 — 复用现有解析数据

What to do: 扩展 HealthReportService 或创建一个新 Service，在菌群报告上传解析完成后，自动将解析结果映射到 health_dimension_scores 表。

现有流程：上传PDF → PdfParseService.parse() → ParsedReportResult → 保存到 HealthReport + HealthGutFlora + HealthIndicator

新增流程：解析完成后 → 调 DimensionScoreService.uploadDataSource() 记录数据源 → 计算维度分数 → 保存到 health_dimension_scores

Step 1: Service 层菌群报告维度计算

在 service/impl/DimensionScoreServiceImpl.java 中新增方法，或创建一个 service/GutReportMappingService.java。这里直接在 DimensionScoreServiceImpl 中新增 processGutReport() 方法：

  // 在 DimensionScoreServiceImpl.java 中新增：

  /** 处理菌群报告解析结果，映射到7维评分 */
  public void processGutReport(Long memberId, ParsedReportResult parsedResult) {
      if (parsedResult == null) return;

      // 创建数据源记录
      DimensionUploadVO uploadVO = new DimensionUploadVO();
      uploadVO.setMemberId(memberId);
      uploadVO.setSourceType("REPORT");
      uploadVO.setDimensionCodes(Arrays.asList("nutrition", "gut", "immunity", "growth", "sleep"));
      uploadVO.setParsedResultJson(parsedResult.toString());
      uploadDataSource(uploadVO);

      // 肠胃健康维度 (从菌群报告最完整获取)
      saveGutScore(memberId, parsedResult);

      // 营养均衡维度
      saveNutritionScore(memberId, parsedResult);

      // 免疫力维度
      saveImmunityScore(memberId, parsedResult);

      // 生长发育维度 (慢性病/易胖风险)
      saveGrowthScore(memberId, parsedResult);

      // 睡眠质量维度 (神经递质)
      saveSleepScore(memberId, parsedResult);

      log.info("菌群报告维度映射完成: memberId={}", memberId);
  }

  private void saveGutScore(Long memberId, ParsedReportResult result) {
      // 肠胃健康 = 综合菌群多项指标加权
      int score = average(
          result.getGutHealthScore(),
          result.getBalanceScore(),
          result.getDiversityScore(),
          result.getBeneficialScore(),
          result.getCoreGenusScore()
      );
      // 如果有有害菌偏高则扣分
      if (result.getHarmfulScore() != null && result.getHarmfulScore() > 60) {
          score = (int)(score * 0.85);
      }
      saveDimensionScore(memberId, "gut", score, 1, "REPORT");
  }

  private void saveNutritionScore(Long memberId, ParsedReportResult result) {
      int score = result.getNutritionScore() != null ? result.getNutritionScore() : 50;
      saveDimensionScore(memberId, "nutrition", score, 1, "REPORT");
  }

  private void saveImmunityScore(Long memberId, ParsedReportResult result) {
      // 免疫力 = 肠道屏障 + 有益菌水平 - 有害菌风险
      int gutHealth = result.getGutHealthScore() != null ? result.getGutHealthScore() : 50;
      int beneficial = result.getBeneficialScore() != null ? result.getBeneficialScore() : 50;
      int harmful = result.getHarmfulScore() != null ? result.getHarmfulScore() : 50;

      int score = (int)(gutHealth * 0.4 + beneficial * 0.4 - (harmful - 50) * 0.5 + 50);
      score = Math.max(0, Math.min(100, score));
      saveDimensionScore(memberId, "immunity", score, 1, "REPORT");
  }

  private void saveGrowthScore(Long memberId, ParsedReportResult result) {
      // 生长发育 = 慢性病控制度 + BMI (BMI在其他数据源中)
      int chronic = result.getChronicDiseaseScore() != null ? result.getChronicDiseaseScore() : 50;
      saveDimensionScore(memberId, "growth", chronic, 1, "REPORT");
  }

  private void saveSleepScore(Long memberId, ParsedReportResult result) {
      // 睡眠质量 = 神经递质指标(从indicators中提取)
      // Phase 1: 如果没有解析出神经递质指标，暂不覆盖
      // 可通过 HealthIndicator category="神经递质" 获取
      // 暂时保留问卷/Tier2数据
      log.info("睡眠维度暂不从菌群报告映射，等待神经递质指标解析完善");
  }

  private void saveDimensionScore(Long memberId, String dimension, int score, int tier, String dataSource) {
      HealthDimensionScore record = new HealthDimensionScore();
      record.setMemberId(memberId);
      record.setDimension(dimension);
      record.setScore(score);
      record.setTier(tier);
      record.setDataSource(dataSource);
      record.setAssessDate(new java.sql.Date(System.currentTimeMillis()));
      healthDimensionScoreService.saveScore(record);
  }

  private int average(Integer... values) {
      int sum = 0, count = 0;
      for (Integer v : values) {
          if (v != null) { sum += v; count++; }
      }
      return count > 0 ? sum / count : 50;
  }

Step 2: 在 HealthReportController 或现有报告处理流程中调用

定位到 /sc-data/cfc/cfc-backend/src/main/java/com/etotem/cfc/controller/HealthReportController.java 的 uploadReport 方法。在 PdfParseService.parse() 调用完成后，获取返回值中的成员ID（subjectId），然后调 dimensionScoreService.processGutReport()。

  // 在 uploadReport 方法中，pdf解析并保存到DB之后添加：

  // 7维健康评分映射 (Phase 1)
  try {
      HealthReport savedReport = /* 刚刚保存的报告 */;
      if (savedReport != null && savedReport.getSubjectId() != null) {
          dimensionScoreService.processGutReport(savedReport.getSubjectId(), parsedReport);
      }
  } catch (Exception e) {
      log.error("菌群报告维度映射失败", e);
      // 不阻断主流程
  }

需要注入 DimensionScoreService:

  @Resource
  private DimensionScoreService dimensionScoreService;

Step 3: 编译验证

mvn clean compile 编译通过

QA Scenarios:

  Scenario: Gut report mapping with existing test PDF
    Tool: Bash (curl)
    Steps:
      1. 启动应用
      2. curl -X POST http://localhost:9082/api/health/report/upload (with test PDF)
      3. curl -X POST http://localhost:9082/api/health/dimensions -H "Authorization: Bearer <token>" -H "Content-Type: application/json" -d '{"memberId": <testMemberId>}'
    Expected Result: dimensions 数组中的 gut/nutrition/immunity/growth 维度有 score 值，dataSource 为 "REPORT"，tier=1
    Evidence: .sisyphus/evidence/task-6-gut-mapping.txt

Commit: YES

Message: feat(health): integrate gut report mapping to dimension scores
Files: cfc-backend/.../service/impl/DimensionScoreServiceImpl.java, controller/HealthReportController.java
[ ] 7. 前端 7维雷达图页面 (health-dimensions.vue)

What to do: 创建 uni-app 页面，展示7维雷达图和每个维度的详情。包括：

雷达图（用 canvas 绘制7边形）
每个维度的分数、等级、数据源标识
点击维度进入问卷填写
上传数据源入口

Step 1: Create pages/body/health-dimensions.vue

/sc-data/cfc/cfc-frontend/pages/body/health-dimensions.vue

  <template>
    <view class="page">
      <!-- 头部 -->
      <view class="header">
        <text class="title">健康画像</text>
        <text class="subtitle">{{ assessDate }} · 基于{{ dataSourceLabel }}评估</text>
      </view>

      <!-- 雷达图区域 -->
      <view class="radar-container">
        <canvas canvas-id="radarCanvas" class="radar-canvas"></canvas>
      </view>

      <!-- 图例 -->
      <view class="legend">
        <view class="legend-item" v-for="dim in dimensions" :key="dim.code">
          <view class="legend-dot" :style="{ background: levelColor(dim.level) }"></view>
          <text class="legend-label">{{ dim.name }}</text>
          <text class="legend-score" :style="{ color: levelColor(dim.level) }">
            {{ dim.score !== null ? dim.score : '--' }}
          </text>
          <text class="legend-percentile" v-if="dim.percentile !== null">
            P{{ dim.percentile }}
          </text>
        </view>
      </view>

      <!-- 操作入口 -->
      <view class="actions">
        <view class="action-btn" @click="showUploadSheet">
          <text class="action-icon">📷</text>
          <text class="action-text">上传报告/照片</text>
        </view>
        <view class="action-btn" @click="showVoiceInput">
          <text class="action-icon">🎤</text>
          <text class="action-text">语音输入</text>
        </view>
      </view>

      <!-- 维度问卷入口 -->
      <view class="dimension-list">
        <view
          class="dimension-card"
          v-for="dim in dimensions"
          :key="dim.code"
          @click="goQuestionnaire(dim)"
        >
          <view class="dim-left">
            <text class="dim-name">{{ dim.name }}</text>
            <text class="dim-desc">{{ dimDesc(dim) }}</text>
          </view>
          <view class="dim-right">
            <view class="dim-score" :style="{ color: levelColor(dim.level) }">
              {{ dim.score !== null ? dim.score : '--' }}
            </view>
            <view class="dim-level" :style="{ background: levelBgColor(dim.level) }">
              {{ dim.levelLabel }}
            </view>
            <text class="dim-source">{{ sourceLabel(dim.tier) }}</text>
          </view>
        </view>
      </view>

      <!-- 上传选项弹窗 -->
      <uni-popup ref="uploadPopup" type="bottom">
        <view class="upload-sheet">
          <view class="sheet-item" @click="uploadPhoto('scale')">
            <text class="sheet-icon">⚖️</text>
            <view>
              <text class="sheet-title">体脂称照片</text>
              <text class="sheet-desc">拍照识别体重/体脂率</text>
            </view>
          </view>
          <view class="sheet-item" @click="uploadPhoto('tongue')">
            <text class="sheet-icon">👅</text>
            <view>
              <text class="sheet-title">舌诊照片</text>
              <text class="sheet-desc">拍照分析肠胃/免疫力</text>
            </view>
          </view>
          <view class="sheet-item" @click="uploadPhoto('exam')">
            <text class="sheet-icon">🏥</text>
            <view>
              <text class="sheet-title">体检报告</text>
              <text class="sheet-desc">拍照自动提取指标</text>
            </view>
          </view>
          <view class="sheet-cancel" @click="hideUploadSheet">取消</view>
        </view>
      </uni-popup>
    </view>
  </template>

  <script>
  const API_BASE = require('../../config').API_BASE_URL

  export default {
    data() {
      return {
        dimensions: [],
        assessDate: '',
        token: ''
      }
    },

    onLoad() {
      this.token = uni.getStorageSync('token')
      this.loadDimensions()
    },

    onReady() {
      // canvas 需要在 onReady 后绘制
      setTimeout(() => this.drawRadar(), 300)
    },

    methods: {
      loadDimensions() {
        uni.request({
          url: API_BASE + '/api/health/dimensions',
          method: 'POST',
          header: { 'Authorization': 'Bearer ' + this.token, 'Content-Type': 'application/json' },
          data: {},
          success: (res) => {
            if (res.data.code === 0) {
              this.dimensions = res.data.data.dimensions || []
              this.assessDate = res.data.data.assessDate || ''
              this.$nextTick(() => this.drawRadar())
            }
          }
        })
      },

      drawRadar() {
        const ctx = uni.createCanvasContext('radarCanvas', this)
        const width = 300
        const height = 300
        const centerX = width / 2
        const centerY = height / 2
        const radius = 120
        const count = this.dimensions.length || 7

        if (count === 0) return

        // 清除
        ctx.clearRect(0, 0, width, height)

        // 绘制网格 (同心多边形)
        const levels = [0.2, 0.4, 0.6, 0.8, 1.0]
        ctx.setStrokeStyle('#e0e0e0')
        ctx.setLineWidth(1)
        for (const l of levels) {
          this.drawPolygon(ctx, centerX, centerY, radius * l, count)
        }

        // 绘制轴线
        ctx.setStrokeStyle('#ccc')
        ctx.setLineWidth(1)
        for (let i = 0; i < count; i++) {
          const angle = (Math.PI * 2 / count) * i - Math.PI / 2
          const x = centerX + radius * Math.cos(angle)
          const y = centerY + radius * Math.sin(angle)
          ctx.beginPath()
          ctx.moveTo(centerX, centerY)
          ctx.lineTo(x, y)
          ctx.stroke()
        }

        // 绘制数据区域
        const validDims = this.dimensions.filter(d => d.score !== null)
        if (validDims.length > 0) {
          ctx.beginPath()
          for (let i = 0; i < count; i++) {
            const dim = this.dimensions[i]
            const value = dim.score !== null ? dim.score / 100 : 0
            const angle = (Math.PI * 2 / count) * i - Math.PI / 2
            const x = centerX + radius * value * Math.cos(angle)
            const y = centerY + radius * value * Math.sin(angle)
            if (i === 0) ctx.moveTo(x, y)
            else ctx.lineTo(x, y)
          }
          ctx.closePath()
          ctx.setFillStyle('rgba(249, 115, 22, 0.2)')
          ctx.setStrokeStyle('#F97316')
          ctx.setLineWidth(2)
          ctx.fill()
          ctx.stroke()
        }

        // 绘制维度标签
        ctx.setFontSize(12)
        ctx.setFillStyle('#333')
        ctx.setTextAlign('center')
        for (let i = 0; i < count; i++) {
          const dim = this.dimensions[i]
          const angle = (Math.PI * 2 / count) * i - Math.PI / 2
          const labelRadius = radius + 25
          const x = centerX + labelRadius * Math.cos(angle)
          const y = centerY + labelRadius * Math.sin(angle)
          ctx.fillText(dim.name, x, y)
        }

        ctx.draw()
      },

      drawPolygon(ctx, cx, cy, r, n) {
        ctx.beginPath()
        for (let i = 0; i < n; i++) {
          const angle = (Math.PI * 2 / n) * i - Math.PI / 2
          const x = cx + r * Math.cos(angle)
          const y = cy + r * Math.sin(angle)
          if (i === 0) ctx.moveTo(x, y)
          else ctx.lineTo(x, y)
        }
        ctx.closePath()
        ctx.stroke()
      },

      levelColor(level) {
        const map = { 'excellent': '#22c55e', 'good': '#86efac', 'average': '#eab308', 'concern': '#ef4444', 'unknown': '#999' }
        return map[level] || '#999'
      },

      levelBgColor(level) {
        const map = { 'excellent': '#dcfce7', 'good': '#f0fdf4', 'average': '#fef9c3', 'concern': '#fee2e2', 'unknown': '#f3f4f6' }
        return map[level] || '#f3f4f6'
      },

      dimDesc(dim) {
        if (dim.score === null) return '尚未评估，点击开始'
        const levelText = { 'excellent': '高于大多数同龄人', 'good': '处于良好水平', 'average': '处于一般水平', 'concern': '建议关注改善' }
        return levelText[dim.level] || '暂无数据'
      },

      sourceLabel(tier) {
        const map = { 1: '自动', 2: '语音', 3: '手动' }
        return map[tier] || ''
      },

      get dataSourceLabel() {
        const maxTier = Math.min(...this.dimensions.map(d => d.tier || 3))
        const map = { 1: '报告/照片', 2: '语音', 3: '手动填写' }
        return map[maxTier] || '手动填写'
      },

      goQuestionnaire(dim) {
        uni.navigateTo({
          url: '/pages/body/questionnaire?dimension=' + dim.code + '&name=' + dim.name
        })
      },

      showUploadSheet() {
        this.$refs.uploadPopup && this.$refs.uploadPopup.open()
      },

      hideUploadSheet() {
        this.$refs.uploadPopup && this.$refs.uploadPopup.close()
      },

      uploadPhoto(type) {
        this.hideUploadSheet()
        uni.chooseImage({
          count: 1,
          success: (res) => {
            const tempPath = res.tempFilePaths[0]
            // Phase 1: 上传照片待OCR服务实现后处理，先提示
            uni.showToast({ title: '照片已接收，解析功能开发中', icon: 'none' })
          }
        })
      },

      showVoiceInput() {
        uni.showToast({ title: '语音输入功能开发中', icon: 'none' })
      }
    }
  }
  </script>

  <style scoped>
  .page { padding: 20rpx 30rpx; background: #f5f5f5; min-height: 100vh; }
  .header { margin-bottom: 30rpx; }
  .title { font-size: 36rpx; font-weight: bold; color: #333; }
  .subtitle { font-size: 24rpx; color: #999; margin-top: 10rpx; display: block; }

  .radar-container { background: #fff; border-radius: 20rpx; padding: 30rpx; margin-bottom: 30rpx; display: flex; justify-content: center; }
  .radar-canvas { width: 600rpx; height: 600rpx; }

  .legend { display: flex; flex-wrap: wrap; gap: 20rpx; margin-bottom: 30rpx; }
  .legend-item { display: flex; align-items: center; gap: 8rpx; background: #fff; padding: 12rpx 20rpx; border-radius: 30rpx; }
  .legend-dot { width: 16rpx; height: 16rpx; border-radius: 50%; }
  .legend-label { font-size: 22rpx; color: #666; }
  .legend-score { font-size: 26rpx; font-weight: bold; }
  .legend-percentile { font-size: 20rpx; color: #999; }

  .actions { display: flex; gap: 20rpx; margin-bottom: 30rpx; }
  .action-btn { flex: 1; display: flex; align-items: center; justify-content: center; gap: 10rpx; background: #fff; padding: 24rpx; border-radius: 16rpx; border: 2rpx solid #eee; }
  .action-icon { font-size: 32rpx; }
  .action-text { font-size: 26rpx; color: #333; }

  .dimension-list { display: flex; flex-direction: column; gap: 16rpx; }
  .dimension-card { display: flex; justify-content: space-between; align-items: center; background: #fff; padding: 24rpx; border-radius: 16rpx; }
  .dim-left { flex: 1; }
  .dim-name { font-size: 28rpx; font-weight: bold; color: #333; display: block; }
  .dim-desc { font-size: 22rpx; color: #999; margin-top: 6rpx; display: block; }
  .dim-right { display: flex; align-items: center; gap: 12rpx; }
  .dim-score { font-size: 36rpx; font-weight: bold; }
  .dim-level { font-size: 20rpx; padding: 4rpx 12rpx; border-radius: 20rpx; }
  .dim-source { font-size: 20rpx; color: #999; }

  .upload-sheet { background: #fff; border-radius: 20rpx 20rpx 0 0; padding: 30rpx; }
  .sheet-item { display: flex; align-items: center; gap: 20rpx; padding: 24rpx 0; border-bottom: 2rpx solid #f0f0f0; }
  .sheet-icon { font-size: 40rpx; }
  .sheet-title { font-size: 28rpx; color: #333; display: block; }
  .sheet-desc { font-size: 22rpx; color: #999; display: block; }
  .sheet-cancel { text-align: center; padding: 24rpx; color: #999; font-size: 28rpx; }
  </style>

Verification:

页面编译正常（uni-app 微信开发者工具导入后无报错）
雷达图渲染正常

QA Scenarios:

  Scenario: Frontend compilation
    Tool: Bash
    Steps:
      1. cd /sc-data/cfc/cfc-frontend && npm install --no-optional 2>/dev/null; npm run dev:mp-weixin 2>&1 | head -10
    Expected Result: 编译成功，无语法错误
    Note: uni-app 可能需要在微信开发者工具中验证实际渲染
    Evidence: .sisyphus/evidence/task-7-frontend.txt

Commit: YES (with Task 8)

Message: feat(health): add health-dimensions page with radar chart and questionnaire entry
Files: cfc-frontend/pages/body/health-dimensions.vue
[ ] 8. 页面路由注册与导航

What to do: 在 pages.json 中注册新页面，并在适当的入口添加导航（如 "身体" Tab 下或 index 页面）。

Step 1: 在 pages.json 中注册

/sc-data/cfc/cfc-frontend/pages.json

在 pages 数组中找到 pages/body/ 相关的条目，在附近添加：

  {
    "path": "pages/body/health-dimensions",
    "style": {
      "navigationBarTitleText": "健康画像"
    }
  }

Step 2: 添加导航入口

在 pages/body/index.vue 或适当的页面中，添加一个入口按钮导航到 health-dimensions 页面：

  <!-- 在某个卡片或按钮中 -->
  <view class="menu-item" @click="goHealthDimensions">
    <text class="menu-icon">📊</text>
    <text class="menu-text">健康画像</text>
    <text class="menu-arrow">›</text>
  </view>

  methods: {
    goHealthDimensions() {
      uni.navigateTo({ url: '/pages/body/health-dimensions' })
    }
  }

具体入口位置需要确认 body/index.vue 的现有布局后确定。基本原则是放在"身体"相关功能区域。

QA Scenarios:

  Scenario: Route registration
    Tool: Bash (grep)
    Steps:
      1. grep '"pages/body/health-dimensions"' /sc-data/cfc/cfc-frontend/pages.json
    Expected Result: 找到路由注册条目
    Evidence: .sisyphus/evidence/task-8-route.txt

Commit: YES (with Task 7)

Message: feat(health): register health-dimensions route and add navigation entry
Files: cfc-frontend/pages.json

Final Verification Wave (MANDATORY — after ALL implementation tasks)

4 review agents run in PARALLEL. ALL must APPROVE. Present consolidated results to user and get explicit "okay" before completing.

Do NOT auto-proceed after verification. Wait for user's explicit approval before marking work complete.

[ ] F1. Plan Compliance Audit — oracle Read the plan end-to-end. For each "Must Have": verify implementation exists (read Java files for entity/Service/Controller methods, check curl endpoint, run mvn compile). For each "Must NOT Have": search for forbidden patterns — reject with file:line if found. Check evidence files exist in .sisyphus/evidence/. Compare deliverables against plan. Output: Must Have [N/N] | Must NOT Have [N/N] | Tasks [N/N] | VERDICT: APPROVE/REJECT
[ ] F2. Code Quality Review — unspecified-high Run mvn clean compile + check for @SuppressWarnings, System.out, e.printStackTrace(), unused imports, missing Serializable on entities. Check AI slop: excessive comments, over-abstraction, generic names (data/result/item/temp). Output: Build [PASS/FAIL] | Files [N clean/N issues] | VERDICT
[ ] F3. Real Manual QA — unspecified-high Start from clean state (fresh DB). Execute EVERY QA scenario from EVERY task — follow exact steps, capture evidence. Test cross-task integration (dimension scoring + gut report mapping). Test edge cases: empty memberId, duplicate submissions. Save to .sisyphus/evidence/final-qa/. Output: Scenarios [N/N pass] | Integration [N/N] | Edge Cases [N tested] | VERDICT
[ ] F4. Scope Fidelity Check — deep For each task: read "What to do", read actual diff (git log/diff). Verify 1:1 — everything in spec was built (no missing), nothing beyond spec was built (no creep). Check "Must NOT do" compliance. Detect cross-task contamination: Task N touching Task M's files. Flag unaccounted changes. Output: Tasks [N/N compliant] | Contamination [CLEAN/N issues] | Unaccounted [CLEAN/N files] | VERDICT

Commit Strategy

Task(s)	Message	Scope
1	`feat(health): add DB migration, dimension entities, and Mappers`	Backend
2	`feat(health): implement HealthDimensionScoreService CRUD`	Backend
3	`feat(health): add norm reference seed data`	Backend
4	`feat(health): implement DimensionScoreService core aggregator`	Backend
5	`feat(health): add HealthDimensionController endpoints`	Backend
6	`feat(health): integrate gut report mapping to dimension scores`	Backend
7	`feat(health): add health-dimensions page with radar chart`	Frontend
8	`feat(health): register health-dimensions route`	Frontend

Success Criteria

Verification Commands

# Backend compilation
cd /sc-data/cfc/cfc-backend && mvn clean compile

# API smoke tests
curl -X POST http://localhost:9082/api/health/dimensions -H "Authorization: Bearer <token>" -H "Content-Type: application/json" -d '{}'
curl -X POST http://localhost:9082/api/health/dimensions/upload -H "Authorization: Bearer <token>" -H "Content-Type: application/json" -d '{"memberId":1,"sourceType":"REPORT","dimensionCodes":["gut","nutrition"]}'
curl -X POST http://localhost:9082/api/health/dimensions/questionnaire -H "Authorization: Bearer <token>" -H "Content-Type: application/json" -d '{"memberId":1,"dimension":"sleep","answers":["1","3","2"]}'

Final Checklist

All 8 backend tasks implemented and compiled
Frontend page renders radar chart
All verification scenarios executed with passing evidence
All "Must Have" present
All "Must NOT Have" absent
F1-F4 all approve
User gives explicit final approval

health-dimensions-phase1-plan.md 70 KB Histórico Em bruto

身体健康7维模型 — Phase 1 实施计划

Context

设计文档

7维代码枚举

数据源优先级

常模百分位颜色

Existing Patterns to Follow

File Structure

New Backend Files

Modified Backend Files

New Frontend Files

Modified Frontend Files

Parallel Execution Waves

TODOs

Final Verification Wave (MANDATORY — after ALL implementation tasks)

Commit Strategy

Success Criteria

Verification Commands

Final Checklist

health-dimensions-phase1-plan.md 70 KB

Histórico Em bruto