Bias Assessor (risk-of-bias, lightweight)
Goal: make evidence quality explicit in a way that is quick, consistent, and auditable.
Inputs
Outputs
Recommended fields
Use a simple 3-level scale (all lowercase): low | unclear | high.
Suggested columns to add (if missing):
- - INLINECODE3
- INLINECODE4
- INLINECODE5
- INLINECODE6
- INLINECODE7
- INLINECODE8
Workflow
- 1. Read
papers/extraction_table.csv and identify the set of included studies. - If RoB columns are missing, add them (keep names stable once introduced).
- For each study, fill each RoB domain:
-
low: design/reporting plausibly controls the bias
-
unclear: not enough information to judge
-
high: clear risk (e.g., missing controls, ambiguous measurement, selective reporting)
- 4. Set
rob_overall conservatively:
-
high if any domain is
high
-
unclear if no
high but at least one
unclear
-
low only if all domains are
low
- 5. Add 1–3 short notes in
rob_notes that justify the rating.
Definition of Done
- - [ ] Every included paper row has all RoB columns filled.
- [ ] Values are strictly from
low|unclear|high (no free-form scale drift). - [ ] Notes are short and specific (what was missing / what was strong).
Troubleshooting
Issue: the table has mixed or inconsistent RoB column names
Fix:
- - Normalize to the recommended column names and keep a single set across all rows.
Issue: the paper lacks enough methodological detail
Fix:
- - Prefer
unclear with a concrete note (“no details on X”) rather than guessing.
偏倚评估器（偏倚风险，轻量版）
目标：以快速、一致且可审计的方式明确证据质量。
输入
- - papers/extraction_table.csv
输出
- - 更新后的 papers/extraction_table.csv
推荐字段
使用简单的三级量表（全小写）：low | unclear | high。
建议添加的列（如缺失）：
- - robselection
- robmeasurement
- robconfounding
- robreporting
- roboverall
- robnotes
工作流程
- 1. 读取 papers/extraction_table.csv 并识别纳入研究集合。
- 若偏倚风险列缺失，则添加（引入后保持列名稳定）。
- 对每项研究，填写每个偏倚风险维度：
- low：研究设计/报告合理控制了该偏倚
- unclear：信息不足以判断
- high：存在明确风险（如缺少对照、测量不明确、选择性报告）
- 4. 保守设置 rob_overall：
- 任一维度为 high 则整体为 high
- 无 high 但至少一个 unclear 则整体为 unclear
- 仅当所有维度均为 low 时整体为 low
- 5. 在 rob_notes 中添加1–3条简短说明，证明评级的合理性。
完成标准
- - [ ] 每篇纳入论文行均已填写所有偏倚风险列。
- [ ] 值严格来自 low|unclear|high（无自由格式量表漂移）。
- [ ] 说明简短且具体（缺失了什么/哪些方面较强）。
故障排除
问题：表格中存在混合或不一致的偏倚风险列名
解决方案：
问题：论文缺乏足够的方法学细节
解决方案：
- - 优先选择 unclear 并附上具体说明（“缺少关于X的细节”），而非进行猜测。
