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scholar-evaluation

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Scholar Evaluation

学术成果评估

Use this skill to evaluate academic or scientific work with a repeatable rubric.
使用该技能，通过可复用的评分准则来评估学术或科研成果。

When to Use

使用场景

  • Reviewing a research paper, proposal, thesis chapter, or literature review.
  • Checking whether claims are supported by cited evidence.
  • Evaluating methodology, study design, analysis, or limitations.
  • Comparing two or more papers for quality or relevance.
  • Producing structured feedback for revision.
  • 评审研究论文、研究提案、论文章节或文献综述。
  • 核查研究结论是否有引用证据支撑。
  • 评估研究方法、研究设计、分析过程或局限性。
  • 对比两篇及以上论文的质量或相关性。
  • 生成结构化的修改反馈意见。

Evaluation Scope

评估范围

Start by identifying the artifact:
  • empirical research paper
  • theoretical paper
  • technical report
  • systematic or narrative literature review
  • research proposal
  • thesis or dissertation chapter
  • conference abstract or short paper
Then choose scope:
  • comprehensive: all rubric dimensions
  • targeted: one or two dimensions, such as method or citations
  • comparative: rank multiple works against the same rubric
首先确定评估对象：
  • 实证研究论文
  • 理论研究论文
  • 技术报告
  • 系统性或叙述性文献综述
  • 研究提案
  • 学位论文章节
  • 会议摘要或短论文
然后选择评估范围：
  • 全面评估：涵盖所有评分准则维度
  • 针对性评估：聚焦一个或两个维度，例如方法或引用
  • 对比评估：基于同一评分准则对多项成果进行排名

Rubric

评分准则

Score each applicable dimension from 1 to 5:
  • 5: excellent; clear, rigorous, and publication-ready
  • 4: good; minor improvements needed
  • 3: adequate; meaningful gaps but usable
  • 2: weak; substantial revision needed
  • 1: poor; major validity or clarity problems
Use 
N/A
for dimensions that do not apply.
对每个适用维度按1-5分打分：
  • 5分：优秀；表述清晰、严谨，达到发表标准
  • 4分：良好；仅需小幅改进
  • 3分：合格；存在明显不足但仍有可用价值
  • 2分：较差；需要大幅修改
  • 1分：糟糕；存在重大有效性或清晰度问题
对于不适用的维度，标记为
N/A
。

1. Problem and Research Question

1. 问题与研究目标

  • Is the problem clear and specific?
  • Is the contribution meaningful?
  • Are scope and assumptions explicit?
  • Does the question match the claimed contribution?
  • 研究问题是否清晰具体？
  • 研究贡献是否有意义？
  • 研究范围与假设是否明确？
  • 研究目标是否与声称的贡献匹配？

2. Literature and Context

2. 文献与研究背景

  • Is relevant prior work covered?
  • Does the work synthesize rather than merely list sources?
  • Are gaps accurately identified?
  • Are recent and foundational sources balanced?
  • 是否涵盖了相关的已有研究成果？
  • 是对文献进行综合分析而非简单罗列吗？
  • 是否准确识别了研究空白？
  • 是否平衡了近期研究与基础研究文献？

3. Methodology

3. 研究方法

  • Does the method answer the research question?
  • Are design choices justified?
  • Are variables, datasets, participants, or materials described clearly?
  • Could another researcher reproduce the work?
  • Are ethical and practical constraints acknowledged?
  • 研究方法能否回应研究目标？
  • 设计选择是否有合理依据？
  • 变量、数据集、研究对象或实验材料的描述是否清晰？
  • 其他研究者能否复现该研究？
  • 是否承认了伦理与实践约束？

4. Data and Evidence

4. 数据与证据

  • Are data sources credible and appropriate?
  • Is sample size or corpus coverage adequate?
  • Are inclusion, exclusion, and preprocessing decisions documented?
  • Are missing data and bias risks discussed?
  • 数据来源是否可信且合适？
  • 样本量或语料库覆盖范围是否充足？
  • 纳入、排除与预处理决策是否有记录？
  • 是否讨论了缺失数据与偏差风险？

5. Analysis

5. 分析过程

  • Are statistical, qualitative, or computational methods appropriate?
  • Are baselines and controls fair?
  • Are uncertainty, sensitivity, or robustness checks included when needed?
  • Are alternative explanations considered?
  • 统计、定性或计算方法是否适用？
  • 基线与对照设置是否合理？
  • 是否根据需要纳入了不确定性、敏感性或稳健性检验？
  • 是否考虑了替代解释？

6. Results and Interpretation

6. 结果与解读

  • Are results clearly presented?
  • Do claims stay within the evidence?
  • Are figures, tables, and metrics understandable?
  • Are negative or null results handled honestly?
  • 结果呈现是否清晰？
  • 结论是否未超出证据支撑范围？
  • 图表与指标是否易于理解？
  • 是否如实处理了阴性或无效结果？

7. Limitations and Threats to Validity

7. 局限性与有效性威胁

  • Are limitations specific rather than generic?
  • Are internal, external, construct, and conclusion-validity risks addressed?
  • Does the paper distinguish speculation from demonstrated results?
  • 局限性是否具体而非泛泛而谈？
  • 是否应对了内部、外部、构念与结论有效性风险？
  • 是否区分了推测与已验证的结果？

8. Writing and Structure

8. 写作与结构

  • Is the argument easy to follow?
  • Are sections organized around the research question?
  • Are definitions and notation clear?
  • Is the tone precise and scholarly?
  • 论证逻辑是否易于理解？
  • 章节是否围绕研究目标组织？
  • 定义与符号是否清晰？
  • 语气是否精准且符合学术规范？

9. Citations

9. 引用情况

  • Do cited papers support the claims attached to them?
  • Are primary sources used where possible?
  • Are reviews labeled as reviews?
  • Are preprints labeled as preprints?
  • Are citation metadata and links correct?
  • 引用的论文是否支撑对应的研究结论？
  • 是否尽可能使用了原始来源？
  • 是否将综述类文献标记为综述？
  • 是否将预印本标记为预印本？
  • 引用元数据与链接是否正确？

Review Process

评审流程

  1. Read the abstract, introduction, figures, and conclusion for claimed contribution.
  2. Read methods and results for evidence quality.
  3. Check the strongest claims against cited sources.
  4. Score each applicable dimension.
  5. Separate critical blockers from revision suggestions.
  6. End with concrete next edits.
  1. 阅读摘要、引言、图表与结论，明确声称的研究贡献。
  2. 阅读方法与结果部分，评估证据质量。
  3. 核查最核心的研究结论是否有引用来源支撑。
  4. 为每个适用维度打分。
  5. 区分关键问题与修改建议。
  6. 给出具体的后续修改方向。

Output Template

输出模板

markdown
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markdown
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Scholar Evaluation: <Artifact>

Scholar Evaluation: <Artifact>

Overall Assessment

Overall Assessment

  • Overall score: <1-5 or N/A>
  • Confidence: <high | medium | low>
  • Summary: <3-5 sentences>
  • Overall score: <1-5 or N/A>
  • Confidence: <high | medium | low>
  • Summary: <3-5 sentences>

Dimension Scores

Dimension Scores

DimensionScoreEvidenceRevision priority
Problem and question
Literature and context
Methodology
Data and evidence
Analysis
Results and interpretation
Limitations
Writing and structure
Citations
DimensionScoreEvidenceRevision priority
Problem and question
Literature and context
Methodology
Data and evidence
Analysis
Results and interpretation
Limitations
Writing and structure
Citations

Critical Issues

Critical Issues

Recommended Revisions

Recommended Revisions

Evidence Checks Needed

Evidence Checks Needed

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Pitfalls

注意事项

  • Do not use the score as a substitute for concrete feedback.
  • Do not penalize a paper for omitting a dimension outside its scope.
  • Do not treat citation count, venue, or author reputation as proof of quality.
  • Do not accept unsupported claims just because they appear in the abstract.
  • 不要用分数替代具体的反馈意见。
  • 不要因成果未涵盖其范围外的维度而扣分。
  • 不要将引用量、发表平台或作者声誉视为质量的证明。
  • 不要仅因摘要中的表述就接受无支撑的结论。