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- 2026年4月3日 02:07
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安装方式
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
检查来源文件
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
菜单
默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill academic-translation-guide命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
基于 SOC 职业分类
正在显示 SKILL.md
| name | academic-translation-guide |
| description | Academic translation, post-editing, and Chinglish correction guide |
| metadata | {"openclaw":{"emoji":"🌐","category":"writing","subcategory":"polish","keywords":["academic translation","machine translation","post-editing","Chinglish correction"],"source":"wentor-research-plugins"}} |
Translate and polish research manuscripts between languages with a focus on academic register, domain-specific terminology, and common pitfalls for Chinese-English academic writing.
| Engine | Strengths | Weaknesses | Best For |
|---|---|---|---|
| DeepL | Excellent European languages, natural output | Limited Asian language pairs | EU language papers |
| Google Translate | Broadest language coverage | Less polished academic register | Quick drafts, rare languages |
| ChatGPT / Claude | Context-aware, follows style instructions | May hallucinate terminology | Post-editing, term-aware translation |
| Tencent TranSmart | Strong Chinese-English technical | Limited other languages | CN-EN STEM papers |
| Baidu Translate | Strong Chinese-English | Less natural English | CN-EN drafts |
# Example: Light post-editing checklist
- [ ] Technical terms are correct and consistent
- [ ] Numbers, units, and chemical formulas are accurate
- [ ] Negation is preserved (a common MT error)
- [ ] Subject-verb agreement is correct
- [ ] Hedging language is appropriate ("may" vs "will")
- [ ] Citations and references are intact
| Chinglish | Correction | Explanation |
|---|---|---|
| "in recent years" (overuse) | "recently" / omit | Direct translation of "近年来", used excessively |
| "play an important role" | varies by context | Direct translation of "起着重要作用", often vague |
| "more and more" | "increasingly" | Direct translation of "越来越" |
| "discuss about" | "discuss" | "discuss" is transitive in English |
| "research on" (as verb) | "investigate" / "study" | "Research" used more as noun in English |
| "the experiment result shows" | "the experimental results show" | Adjective form + plural |
| "according to" (overuse) | "based on" / rephrase | Direct translation of "根据" |
Problem: Topic-comment structure (Chinese) vs. Subject-verb-object (English)
Chinglish: "This method, its advantage is that it can process large datasets."
Correct: "The advantage of this method is its ability to process large datasets."
Problem: Missing articles (a, an, the)
Chinglish: "We propose method to solve problem."
Correct: "We propose a method to solve the problem."
Problem: Redundant phrasing
Chinglish: "In this paper, we propose a novel new method..."
Correct: "We propose a novel method..." (or "a new method")
Chinglish: "The purpose of this study is to study..."
Correct: "This study investigates..."
Problem: Overuse of passive voice
Chinglish: "It was found by us that the results were improved by the new method."
Correct: "We found that the new method improved the results."
| Informal | Formal Academic |
|---|---|
| "a lot of" | "numerous" / "substantial" |
| "get" | "obtain" / "achieve" |
| "big" | "significant" / "substantial" |
| "show" | "demonstrate" / "indicate" |
| "think" | "hypothesize" / "propose" |
| "look at" | "examine" / "investigate" |
| "pretty good" | "satisfactory" / "promising" |
| "kind of" | "somewhat" / "to some extent" |
Academic writing requires appropriate hedging to avoid overclaiming:
Too strong: "This proves that X causes Y."
Hedged: "These results suggest that X may contribute to Y."
Too strong: "It is certain that..."
Hedged: "It appears likely that..." / "The evidence indicates..."
Too strong: "All researchers agree..."
Hedged: "There is broad consensus that..." / "Most studies suggest..."
For each paper, maintain a bilingual glossary to ensure consistency:
| Chinese Term | English Term | Domain | Notes |
|-------------|-------------|--------|-------|
| 深度学习 | deep learning | CS/AI | not "depth learning" |
| 损失函数 | loss function | ML | not "lost function" |
| 显著性 | significance | Stats | statistical significance |
| 显著性 | saliency | CV | visual saliency (different!) |
| 鲁棒性 | robustness | General | not "robust nature" |
| 过拟合 | overfitting | ML | not "over-fitting" (no hyphen) |
| 特征提取 | feature extraction | ML/CV | |
| 基准测试 | benchmark | CS | not "base test" |
prompt = """Translate the following Chinese academic abstract to English.
Requirements:
1. Use formal academic register
2. Maintain these specific translations:
- 注意力机制 -> attention mechanism
- 自监督学习 -> self-supervised learning
- 下游任务 -> downstream task
3. Do not add information not present in the original
4. Preserve all citation markers like [1], [2]
Chinese text:
{source_text}
"""
After translating and editing, verify: