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science-reproducibility

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Use before reporting any experiment result, when a result cannot be re-run, when writing the methods section, or when preparing a reproducibility package; covers run provenance, environment capture, seed handling, artifact hashing, and the clean-room re-run check.

dsh-science/skills/science/science-reproducibility/SKILL.md

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# 可复现性（运行留痕与干净重跑）

## 何时用
- 每次要对外报告一个实验结论之前；
- 方法学部分动笔之前（先把该记的记下来）；
- 有人质疑结果、或自己发现两次运行不一致时。

## 前置检查
1. 项目是否已 `science_project_open`（没有 project_id 的运行记录没有归属）；
2. 实验计划是否已 `science_exp_plan`（预注册式：假设、变量、n、分析计划、风险）；
3. 工作目录是否在 git 仓库内（能拿到 commit 才能谈复现）。

## 步骤
1. **固定环境**：记录解释器版本、关键依赖版本（`pip freeze` / `renv.lock` / `package-lock.json`）并算一个依赖哈希；不要只写"用了 pandas"。
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