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Scientific Critical Evaluation and Peer Review

科学批判性评估与同行评审

Overview

概述

Peer review is a systematic process for evaluating scientific manuscripts. Assess methodology, statistics, design, reproducibility, ethics, and reporting standards. Apply this skill for manuscript and grant review across disciplines with constructive, rigorous evaluation.
同行评审是评估科学手稿的系统性流程。评估内容包括方法论、统计学、研究设计、可重复性、伦理规范及报告标准。将此技能应用于跨学科的手稿与基金申请评审，提供具有建设性、严谨性的评估。

When to Use This Skill

何时使用此技能

This skill should be used when:
  • Conducting peer review of scientific manuscripts for journals
  • Evaluating grant proposals and research applications
  • Assessing methodology and experimental design rigor
  • Reviewing statistical analyses and reporting standards
  • Evaluating reproducibility and data availability
  • Checking compliance with reporting guidelines (CONSORT, STROBE, PRISMA)
  • Providing constructive feedback on scientific writing
在以下场景中应使用此技能：
  • 为期刊进行科学手稿的同行评审
  • 评估基金提案与研究申请
  • 评估方法论与实验设计的严谨性
  • 审查统计分析与报告标准
  • 评估可重复性与数据可用性
  • 检查是否符合报告指南（CONSORT、STROBE、PRISMA）
  • 为科学写作提供建设性反馈

Visual Enhancement with Scientific Schematics

借助科学示意图增强可视化效果

When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
If your document does not already contain schematics or diagrams:
  • Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
  • Simply describe your desired diagram in natural language
  • Nano Banana Pro will automatically generate, review, and refine the schematic
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
  • Create publication-quality images with proper formatting
  • Review and refine through multiple iterations
  • Ensure accessibility (colorblind-friendly, high contrast)
  • Save outputs in the figures/ directory
When to add schematics:
  • Peer review workflow diagrams
  • Evaluation criteria decision trees
  • Review process flowcharts
  • Methodology assessment frameworks
  • Quality assessment visualizations
  • Reporting guidelines compliance diagrams
  • Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
使用此技能创建文档时，始终考虑添加科学图表与示意图以提升视觉传达效果。
如果你的文档尚未包含示意图或图表：
  • 使用scientific-schematics技能生成AI驱动的出版级图表
  • 只需用自然语言描述你想要的图表
  • Nano Banana Pro会自动生成、审查并优化示意图
对于新文档： 默认应生成科学示意图，以可视化呈现文本中描述的关键概念、工作流、架构或关系。
如何生成示意图：
bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
AI将自动：
  • 创建格式规范的出版级图片
  • 通过多轮迭代审查与优化
  • 确保可访问性（色盲友好、高对比度）
  • 将输出保存至figures/目录
何时添加示意图：
  • 同行评审工作流图表
  • 评估标准决策树
  • 评审流程流程图
  • 方法论评估框架
  • 质量评估可视化图
  • 报告指南合规性图表
  • 任何需要可视化的复杂概念
有关创建示意图的详细指南，请参考scientific-schematics技能文档。

Peer Review Workflow

同行评审工作流

Conduct peer review systematically through the following stages, adapting depth and focus based on the manuscript type and discipline.
通过以下阶段系统性开展同行评审，根据手稿类型与学科调整评估深度与重点。

Stage 1: Initial Assessment

阶段1：初步评估

Begin with a high-level evaluation to determine the manuscript's scope, novelty, and overall quality.
Key Questions:
  • What is the central research question or hypothesis?
  • What are the main findings and conclusions?
  • Is the work scientifically sound and significant?
  • Is the work appropriate for the intended venue?
  • Are there any immediate major flaws that would preclude publication?
Output: Brief summary (2-3 sentences) capturing the manuscript's essence and initial impression.
从高层级评估开始，确定手稿的范围、创新性与整体质量。
核心问题：
  • 核心研究问题或假设是什么？
  • 主要发现与结论是什么？
  • 研究工作是否科学合理且具有重要性？
  • 研究工作是否适合目标发表渠道？
  • 是否存在任何会阻碍发表的重大缺陷？
输出： 简短摘要（2-3句话），概括手稿的核心内容与初步印象。

Stage 2: Detailed Section-by-Section Review

阶段2：逐节详细评审

Conduct a thorough evaluation of each manuscript section, documenting specific concerns and strengths.
对手稿的每个部分进行全面评估，记录具体问题与优势。

Abstract and Title

摘要与标题

  • Accuracy: Does the abstract accurately reflect the study's content and conclusions?
  • Clarity: Is the title specific, accurate, and informative?
  • Completeness: Are key findings and methods summarized appropriately?
  • Accessibility: Is the abstract comprehensible to a broad scientific audience?
  • 准确性： 摘要是否准确反映研究内容与结论？
  • 清晰度： 标题是否具体、准确且信息丰富？
  • 完整性： 关键发现与方法是否得到恰当总结？
  • 易读性： 摘要是否能被广泛的科学受众理解？

Introduction

引言

  • Context: Is the background information adequate and current?
  • Rationale: Is the research question clearly motivated and justified?
  • Novelty: Is the work's originality and significance clearly articulated?
  • Literature: Are relevant prior studies appropriately cited?
  • Objectives: Are research aims/hypotheses clearly stated?
  • 背景： 背景信息是否充分且与时俱进？
  • 合理性： 研究问题是否得到清晰阐述与论证？
  • 创新性： 研究工作的原创性与重要性是否清晰说明？
  • 文献： 相关前期研究是否得到恰当引用？
  • 目标： 研究目标/假设是否清晰陈述？

Methods

方法

  • Reproducibility: Can another researcher replicate the study from the description provided?
  • Rigor: Are the methods appropriate for addressing the research questions?
  • Detail: Are protocols, reagents, equipment, and parameters sufficiently described?
  • Ethics: Are ethical approvals, consent, and data handling properly documented?
  • Statistics: Are statistical methods appropriate, clearly described, and justified?
  • Validation: Are controls, replicates, and validation approaches adequate?
Critical elements to verify:
  • Sample sizes and power calculations
  • Randomization and blinding procedures
  • Inclusion/exclusion criteria
  • Data collection protocols
  • Computational methods and software versions
  • Statistical tests and correction for multiple comparisons
  • 可重复性： 其他研究人员能否根据所提供的描述重复该研究？
  • 严谨性： 方法是否适合解决研究问题？
  • 细节： 实验方案、试剂、设备与参数是否描述充分？
  • 伦理： 伦理审批、知情同意与数据处理是否有恰当记录？
  • 统计学： 统计方法是否恰当、描述清晰且有合理依据？
  • 验证： 对照、重复与验证方法是否充分？
需验证的关键要素：
  • 样本量与功效计算
  • 随机化与盲法流程
  • 纳入/排除标准
  • 数据收集方案
  • 计算方法与软件版本
  • 统计检验与多重比较校正

Results

结果

  • Presentation: Are results presented logically and clearly?
  • Figures/Tables: Are visualizations appropriate, clear, and properly labeled?
  • Statistics: Are statistical results properly reported (effect sizes, confidence intervals, p-values)?
  • Objectivity: Are results presented without over-interpretation?
  • Completeness: Are all relevant results included, including negative results?
  • Reproducibility: Are raw data or summary statistics provided?
Common issues to identify:
  • Selective reporting of results
  • Inappropriate statistical tests
  • Missing error bars or measures of variability
  • Over-fitting or circular analysis
  • Batch effects or confounding variables
  • Missing controls or validation experiments
  • 呈现方式： 结果是否逻辑清晰地呈现？
  • 图表/表格： 可视化是否恰当、清晰且标注规范？
  • 统计学： 统计结果是否正确报告（效应量、置信区间、p值）？
  • 客观性： 结果是否无过度解读？
  • 完整性： 是否包含所有相关结果，包括阴性结果？
  • 可重复性： 是否提供原始数据或汇总统计数据？
需识别的常见问题：
  • 选择性报告结果
  • 不恰当的统计检验
  • 缺少误差线或变异性衡量指标
  • 过拟合或循环分析
  • 批次效应或混杂变量
  • 缺少对照或验证实验

Discussion

讨论

  • Interpretation: Are conclusions supported by the data?
  • Limitations: Are study limitations acknowledged and discussed?
  • Context: Are findings placed appropriately within existing literature?
  • Speculation: Is speculation clearly distinguished from data-supported conclusions?
  • Significance: Are implications and importance clearly articulated?
  • Future directions: Are next steps or unanswered questions discussed?
Red flags:
  • Overstated conclusions
  • Ignoring contradictory evidence
  • Causal claims from correlational data
  • Inadequate discussion of limitations
  • Mechanistic claims without mechanistic evidence
  • 解读： 结论是否有数据支持？
  • 局限性： 是否承认并讨论研究局限性？
  • 背景： 研究结果是否恰当地置于现有文献中？
  • 推测： 推测是否与数据支持的结论明确区分？
  • 重要性： 是否清晰阐述研究意义与影响？
  • 未来方向： 是否讨论下一步研究或未解决的问题？
警示信号：
  • 结论夸大
  • 忽略矛盾证据
  • 从相关性数据得出因果结论
  • 对局限性讨论不足
  • 无机制证据却提出机制性主张

References

参考文献

  • Completeness: Are key relevant papers cited?
  • Currency: Are recent important studies included?
  • Balance: Are contrary viewpoints appropriately cited?
  • Accuracy: Are citations accurate and appropriate?
  • Self-citation: Is there excessive or inappropriate self-citation?
  • 完整性： 关键相关论文是否已引用？
  • 时效性： 是否包含近期重要研究？
  • 平衡性： 是否恰当引用相反观点？
  • 准确性： 引用是否准确且恰当？
  • 自引： 是否存在过度或不恰当的自引？

Stage 3: Methodological and Statistical Rigor

阶段3：方法论与统计严谨性

Evaluate the technical quality and rigor of the research with particular attention to common pitfalls.
Statistical Assessment:
  • Are statistical assumptions met (normality, independence, homoscedasticity)?
  • Are effect sizes reported alongside p-values?
  • Is multiple testing correction applied appropriately?
  • Are confidence intervals provided?
  • Is sample size justified with power analysis?
  • Are parametric vs. non-parametric tests chosen appropriately?
  • Are missing data handled properly?
  • Are exploratory vs. confirmatory analyses distinguished?
Experimental Design:
  • Are controls appropriate and adequate?
  • Is replication sufficient (biological and technical)?
  • Are potential confounders identified and controlled?
  • Is randomization properly implemented?
  • Are blinding procedures adequate?
  • Is the experimental design optimal for the research question?
Computational/Bioinformatics:
  • Are computational methods clearly described and justified?
  • Are software versions and parameters documented?
  • Is code made available for reproducibility?
  • Are algorithms and models validated appropriately?
  • Are assumptions of computational methods met?
  • Is batch correction applied appropriately?
评估研究的技术质量与严谨性，特别关注常见陷阱。
统计评估：
  • 是否满足统计假设（正态性、独立性、方差齐性）？
  • 是否在报告p值的同时报告效应量？
  • 是否恰当应用多重检验校正？
  • 是否提供置信区间？
  • 是否通过功效分析证明样本量合理？
  • 参数检验与非参数检验的选择是否恰当？
  • 缺失数据处理是否得当？
  • 是否区分探索性分析与验证性分析？
实验设计：
  • 对照是否恰当且充分？
  • 重复是否足够（生物学重复与技术重复）？
  • 是否识别并控制潜在混杂因素？
  • 随机化是否正确实施？
  • 盲法流程是否充分？
  • 实验设计是否最适合研究问题？
计算/生物信息学：
  • 计算方法是否清晰描述且有合理依据？
  • 是否记录软件版本与参数？
  • 是否提供代码以确保可重复性？
  • 算法与模型是否经过恰当验证？
  • 是否满足计算方法的假设？
  • 是否恰当应用批次校正？

Stage 4: Reproducibility and Transparency

阶段4：可重复性与透明度

Assess whether the research meets modern standards for reproducibility and open science.
Data Availability:
  • Are raw data deposited in appropriate repositories?
  • Are accession numbers provided for public databases?
  • Are data sharing restrictions justified (e.g., patient privacy)?
  • Are data formats standard and accessible?
Code and Materials:
  • Is analysis code made available (GitHub, Zenodo, etc.)?
  • Are unique materials available or described sufficiently for recreation?
  • Are protocols detailed in sufficient depth?
Reporting Standards:
  • Does the manuscript follow discipline-specific reporting guidelines (CONSORT, PRISMA, ARRIVE, MIAME, MINSEQE, etc.)?
  • See 
    references/reporting_standards.md
    for common guidelines
  • Are all elements of the appropriate checklist addressed?
评估研究是否符合现代可重复性与开放科学标准。
数据可用性：
  • 原始数据是否存入合适的数据库？
  • 是否提供公共数据库的登录号？
  • 数据共享限制是否有合理依据（如患者隐私）？
  • 数据格式是否标准且可访问？
代码与材料：
  • 分析代码是否公开可用（GitHub、Zenodo等）？
  • 独特材料是否可获取或描述足够详细以重现？
  • 实验方案描述是否足够详细？
报告标准：
  • 手稿是否遵循学科特定的报告指南（CONSORT、PRISMA、ARRIVE、MIAME、MINSEQE等）？
  • 常见指南请参考
    references/reporting_standards.md
  • 是否涵盖相应清单的所有要素？

Stage 5: Figure and Data Presentation

阶段5：图表与数据呈现

Evaluate the quality, clarity, and integrity of data visualization.
Quality Checks:
  • Are figures high resolution and clearly labeled?
  • Are axes properly labeled with units?
  • Are error bars defined (SD, SEM, CI)?
  • Are statistical significance indicators explained?
  • Are color schemes appropriate and accessible (colorblind-friendly)?
  • Are scale bars included for images?
  • Is data visualization appropriate for the data type?
Integrity Checks:
  • Are there signs of image manipulation (duplications, splicing)?
  • Are Western blots and gels appropriately presented?
  • Are representative images truly representative?
  • Are all conditions shown (no selective presentation)?
Clarity:
  • Can figures stand alone with their legends?
  • Is the message of each figure immediately clear?
  • Are there redundant figures or panels?
  • Would data be better presented as tables or figures?
评估数据可视化的质量、清晰度与完整性。
质量检查：
  • 图表是否高分辨率且标注清晰？
  • 坐标轴是否标注单位？
  • 误差线是否定义（SD、SEM、CI）？
  • 统计显著性标识是否有说明？
  • 配色方案是否恰当且可访问（色盲友好）？
  • 图像是否包含比例尺？
  • 数据可视化是否适合数据类型？
完整性检查：
  • 是否存在图像操纵迹象（重复、拼接）？
  • Western blot与凝胶呈现是否恰当？
  • 代表性图像是否真正具有代表性？
  • 是否展示所有条件（无选择性呈现）？
清晰度：
  • 图表是否可独立于图例理解？
  • 每个图表的核心信息是否一目了然？
  • 是否存在冗余图表或面板？
  • 数据是否更适合以表格或图表呈现？

Stage 6: Ethical Considerations

阶段6：伦理考量

Verify that the research meets ethical standards and guidelines.
Human Subjects:
  • Is IRB/ethics approval documented?
  • Is informed consent described?
  • Are vulnerable populations appropriately protected?
  • Is patient privacy adequately protected?
  • Are potential conflicts of interest disclosed?
Animal Research:
  • Is IACUC or equivalent approval documented?
  • Are procedures humane and justified?
  • Are the 3Rs (replacement, reduction, refinement) considered?
  • Are euthanasia methods appropriate?
Research Integrity:
  • Are there concerns about data fabrication or falsification?
  • Is authorship appropriate and justified?
  • Are competing interests disclosed?
  • Is funding source disclosed?
  • Are there concerns about plagiarism or duplicate publication?
验证研究是否符合伦理标准与指南。
人类受试者：
  • 是否记录IRB/伦理审批？
  • 是否描述知情同意？
  • 弱势群体是否得到恰当保护？
  • 患者隐私是否得到充分保护？
  • 是否披露潜在利益冲突？
动物研究：
  • 是否记录IACUC或等效机构的审批？
  • 实验流程是否人道且有合理依据？
  • 是否考虑3Rs原则（替代、减少、优化）？
  • 安乐死方法是否恰当？
研究诚信：
  • 是否存在数据捏造或篡改的疑虑？
  • 作者资格是否恰当且有合理依据？
  • 是否披露利益冲突？
  • 是否披露资金来源？
  • 是否存在剽窃或重复发表的疑虑？

Stage 7: Writing Quality and Clarity

阶段7：写作质量与清晰度

Assess the manuscript's clarity, organization, and accessibility.
Structure and Organization:
  • Is the manuscript logically organized?
  • Do sections flow coherently?
  • Are transitions between ideas clear?
  • Is the narrative compelling and clear?
Writing Quality:
  • Is the language clear, precise, and concise?
  • Are jargon and acronyms minimized and defined?
  • Is grammar and spelling correct?
  • Are sentences unnecessarily complex?
  • Is the passive voice overused?
Accessibility:
  • Can a non-specialist understand the main findings?
  • Are technical terms explained?
  • Is the significance clear to a broad audience?
评估手稿的清晰度、组织结构与易读性。
结构与组织：
  • 手稿逻辑是否清晰？
  • 各部分衔接是否连贯？
  • 观点过渡是否清晰？
  • 叙述是否引人入胜且清晰易懂？
写作质量：
  • 语言是否清晰、准确且简洁？
  • 术语与缩写是否尽量减少并定义？
  • 语法与拼写是否正确？
  • 句子是否过于复杂？
  • 被动语态是否过度使用？
可访问性：
  • 非专业人士能否理解主要发现？
  • 技术术语是否有解释？
  • 研究意义是否为广泛受众清晰理解？

Structuring Peer Review Reports

同行评审报告结构

Organize feedback in a hierarchical structure that prioritizes issues and provides actionable guidance.
以层级结构组织反馈，优先列出问题并提供可操作的指导。

Summary Statement

总结陈述

Provide a concise overall assessment (1-2 paragraphs):
  • Brief synopsis of the research
  • Overall recommendation (accept, minor revisions, major revisions, reject)
  • Key strengths (2-3 bullet points)
  • Key weaknesses (2-3 bullet points)
  • Bottom-line assessment of significance and soundness
提供简洁的整体评估（1-2段）：
  • 研究内容的简要概述
  • 总体建议（接受、小修、大修、拒稿）
  • 核心优势（2-3个要点）
  • 核心劣势（2-3个要点）
  • 对研究重要性与科学性的最终评估

Major Comments

主要意见

List critical issues that significantly impact the manuscript's validity, interpretability, or significance. Number these sequentially for easy reference.
Major comments typically include:
  • Fundamental methodological flaws
  • Inappropriate statistical analyses
  • Unsupported or overstated conclusions
  • Missing critical controls or experiments
  • Serious reproducibility concerns
  • Major gaps in literature coverage
  • Ethical concerns
For each major comment:
  1. Clearly state the issue
  2. Explain why it's problematic
  3. Suggest specific solutions or additional experiments
  4. Indicate if addressing it is essential for publication
列出严重影响手稿有效性、可解释性或重要性的关键问题。按顺序编号以便参考。
主要意见通常包括：
  • 根本性方法论缺陷
  • 不恰当的统计分析
  • 无依据或夸大的结论
  • 缺少关键对照或实验
  • 严重的可重复性问题
  • 文献覆盖存在重大缺口
  • 伦理问题
针对每个主要意见：
  1. 清晰陈述问题
  2. 解释问题的严重性
  3. 建议具体解决方案或补充实验
  4. 说明解决该问题是否为发表的必要条件

Minor Comments

次要意见

List less critical issues that would improve clarity, completeness, or presentation. Number these sequentially.
Minor comments typically include:
  • Unclear figure labels or legends
  • Missing methodological details
  • Typographical or grammatical errors
  • Suggestions for improved data presentation
  • Minor statistical reporting issues
  • Supplementary analyses that would strengthen conclusions
  • Requests for clarification
For each minor comment:
  1. Identify the specific location (section, paragraph, figure)
  2. State the issue clearly
  3. Suggest how to address it
列出对清晰度、完整性或呈现方式有帮助但不关键的问题。按顺序编号。
次要意见通常包括：
  • 图表标签或图例不清晰
  • 缺少方法论细节
  • 排版或语法错误
  • 数据呈现优化建议
  • 次要统计报告问题
  • 可强化结论的补充分析
  • 澄清请求
针对每个次要意见：
  1. 指明具体位置（章节、段落、图表）
  2. 清晰陈述问题
  3. 建议解决方法

Specific Line-by-Line Comments (Optional)

逐行具体意见（可选）

For manuscripts requiring detailed feedback, provide section-specific or line-by-line comments:
  • Reference specific page/line numbers or sections
  • Note factual errors, unclear statements, or missing citations
  • Suggest specific edits for clarity
对于需要详细反馈的手稿，提供章节特定或逐行意见：
  • 参考具体页码/行号或章节
  • 指出事实错误、表述不清或缺少引用
  • 建议具体的编辑修改以提升清晰度

Questions for Authors

向作者提出的问题

List specific questions that need clarification:
  • Methodological details that are unclear
  • Seemingly contradictory results
  • Missing information needed to evaluate the work
  • Requests for additional data or analyses
列出需要澄清的具体问题：
  • 不清晰的方法论细节
  • 看似矛盾的结果
  • 评估工作所需的缺失信息
  • 对补充数据或分析的请求

Tone and Approach

语气与方法

Maintain a constructive, professional, and collegial tone throughout the review.
Best Practices:
  • Be constructive: Frame criticism as opportunities for improvement
  • Be specific: Provide concrete examples and actionable suggestions
  • Be balanced: Acknowledge strengths as well as weaknesses
  • Be respectful: Remember that authors have invested significant effort
  • Be objective: Focus on the science, not the scientists
  • Be thorough: Don't overlook issues, but prioritize appropriately
  • Be clear: Avoid ambiguous or vague criticism
Avoid:
  • Personal attacks or dismissive language
  • Sarcasm or condescension
  • Vague criticism without specific examples
  • Requesting unnecessary experiments beyond the scope
  • Demanding adherence to personal preferences vs. best practices
  • Revealing your identity if reviewing is double-blind
在整个评审过程中保持建设性、专业与协作的语气。
最佳实践：
  • 建设性： 将批评转化为改进机会
  • 具体： 提供具体示例与可操作建议
  • 平衡： 同时认可优势与劣势
  • 尊重： 记住作者投入了大量精力
  • 客观： 关注科学内容而非研究者
  • 全面： 不要忽略问题，但要合理排序优先级
  • 清晰： 避免模糊或含糊的批评
需避免：
  • 人身攻击或轻蔑语言
  • 讽刺或居高临下的态度
  • 无具体示例的模糊批评
  • 请求超出研究范围的不必要实验
  • 要求遵循个人偏好而非最佳实践
  • 双盲评审时暴露自己的身份

Special Considerations by Manuscript Type

按手稿类型的特殊考量

Original Research Articles

原创研究文章

  • Emphasize rigor, reproducibility, and novelty
  • Assess significance and impact
  • Verify that conclusions are data-driven
  • Check for complete methods and appropriate controls
  • 强调严谨性、可重复性与创新性
  • 评估重要性与影响力
  • 验证结论是否基于数据
  • 检查方法是否完整、对照是否恰当

Reviews and Meta-Analyses

综述与元分析

  • Evaluate comprehensiveness of literature coverage
  • Assess search strategy and inclusion/exclusion criteria
  • Verify systematic approach and lack of bias
  • Check for critical analysis vs. mere summarization
  • For meta-analyses, evaluate statistical approach and heterogeneity
  • 评估文献覆盖的全面性
  • 评估检索策略与纳入/排除标准
  • 验证系统性方法与无偏性
  • 区分批判性分析与单纯总结
  • 对于元分析，评估统计方法与异质性

Methods Papers

方法学论文

  • Emphasize validation and comparison to existing methods
  • Assess reproducibility and availability of protocols/code
  • Evaluate improvements over existing approaches
  • Check for sufficient detail for implementation
  • 强调验证与与现有方法的比较
  • 评估可重复性与实验方案/代码的可用性
  • 评估对现有方法的改进
  • 检查实现所需的细节是否充分

Short Reports/Letters

短篇报告/快报

  • Adapt expectations for brevity
  • Ensure core findings are still rigorous and significant
  • Verify that format is appropriate for findings
  • 根据简洁性调整期望
  • 确保核心发现仍严谨且重要
  • 验证格式是否适合研究结果

Preprints

预印本

  • Recognize that these have not undergone formal peer review
  • May be less polished than journal submissions
  • Still apply rigorous standards for scientific validity
  • Consider providing constructive feedback to help authors improve before journal submission
  • 认识到这些尚未经过正式同行评审
  • 可能不如期刊投稿打磨完善
  • 仍需应用严格的科学有效性标准
  • 考虑提供建设性反馈以帮助作者在投稿期刊前改进

Presentations and Slide Decks

演示文稿与幻灯片

⚠️ CRITICAL: For presentations, NEVER read the PDF directly. ALWAYS convert to images first.
When reviewing scientific presentations (PowerPoint, Beamer, slide decks):
⚠️ 重要提示： 对于演示文稿，切勿直接读取PDF。务必先转换为图像。
评审科学演示文稿（PowerPoint、Beamer、幻灯片）时：

Mandatory Image-Based Review Workflow

基于图像的强制评审工作流

NEVER attempt to read presentation PDFs directly - this causes buffer overflow errors and doesn't show visual formatting issues.
Required Process:
  1. Convert PDF to images using Python:
    bash
    python skills/scientific-slides/scripts/pdf_to_images.py presentation.pdf review/slide --dpi 150
# Creates: review/slide-001.jpg, review/slide-002.jpg, etc.
  2. Read and inspect EACH slide image file sequentially
  3. Document issues with specific slide numbers
  4. Provide feedback on visual formatting and content
Print when starting review:
[HH:MM:SS] PEER REVIEW: Presentation detected - converting to images for review
[HH:MM:SS] PDF REVIEW: NEVER reading PDF directly - using image-based inspection
切勿尝试直接读取演示文稿PDF - 这会导致缓冲区溢出错误，且无法发现视觉格式问题。
必需流程：
  1. 使用Python将PDF转换为图像：
    bash
    python skills/scientific-slides/scripts/pdf_to_images.py presentation.pdf review/slide --dpi 150
# 生成：review/slide-001.jpg, review/slide-002.jpg等
  2. 依次读取并检查每张幻灯片图像文件
  3. 记录具体幻灯片编号对应的问题
  4. 提供视觉格式与内容方面的反馈
开始评审时打印：
[HH:MM:SS] PEER REVIEW: Presentation detected - converting to images for review
[HH:MM:SS] PDF REVIEW: NEVER reading PDF directly - using image-based inspection

Presentation-Specific Evaluation Criteria

演示文稿特定评估标准

Visual Design and Readability:
  • Text is large enough (minimum 18pt, ideally 24pt+ for body text)
  • High contrast between text and background (4.5:1 minimum, 7:1 preferred)
  • Color scheme is professional and colorblind-accessible
  • Consistent visual design across all slides
  • White space is adequate (not cramped)
  • Fonts are clear and professional
Layout and Formatting (Check EVERY Slide Image):
  • No text overflow or truncation at slide edges
  • No element overlaps (text over images, overlapping shapes)
  • Titles are consistently positioned
  • Content is properly aligned
  • Bullets and text are not cut off
  • Figures fit within slide boundaries
  • Captions and labels are visible and readable
Content Quality:
  • One main idea per slide (not overloaded)
  • Minimal text (3-6 bullets per slide maximum)
  • Bullet points are concise (5-7 words each)
  • Figures are simplified and clear (not copy-pasted from papers)
  • Data visualizations have large, readable labels
  • Citations are present and properly formatted
  • Results/data slides dominate the presentation (40-50% of content)
Structure and Flow:
  • Clear narrative arc (introduction → methods → results → discussion)
  • Logical progression between slides
  • Slide count appropriate for talk duration (~1 slide per minute)
  • Title slide includes authors, affiliation, date
  • Introduction cites relevant background literature (3-5 papers)
  • Discussion cites comparison papers (3-5 papers)
  • Conclusions slide summarizes key findings
  • Acknowledgments/funding slide at end
Scientific Content:
  • Research question clearly stated
  • Methods adequately summarized (not excessive detail)
  • Results presented logically with clear visualizations
  • Statistical significance indicated appropriately
  • Conclusions supported by data shown
  • Limitations acknowledged where appropriate
  • Future directions or broader impact discussed
Common Presentation Issues to Flag:
Critical Issues (Must Fix):
  • Text overflow making content unreadable
  • Font sizes too small (<18pt)
  • Element overlaps obscuring data
  • Insufficient contrast (text hard to read)
  • Figures too complex or illegible
  • No citations (completely unsupported claims)
  • Slide count drastically mismatched to duration
Major Issues (Should Fix):
  • Inconsistent design across slides
  • Too much text (walls of text, not bullets)
  • Poorly simplified figures (axis labels too small)
  • Cramped layout with insufficient white space
  • Missing key structural elements (no conclusion slide)
  • Poor color choices (not colorblind-safe)
  • Minimal results content (<30% of slides)
Minor Issues (Suggestions for Improvement):
  • Could use more visuals/diagrams
  • Some slides slightly text-heavy
  • Minor alignment inconsistencies
  • Could benefit from more white space
  • Additional citations would strengthen claims
  • Color scheme could be more modern
视觉设计与可读性：
  • 文本足够大（最小18pt，正文理想为24pt+）
  • 文本与背景对比度高（最小4.5:1，首选7:1）
  • 配色方案专业且色盲友好
  • 所有幻灯片视觉设计一致
  • 留白充足（不拥挤）
  • 字体清晰专业
布局与格式（检查每张幻灯片图像）：
  • 无文本溢出或截断至幻灯片边缘
  • 无元素重叠（文本覆盖图像、形状重叠）
  • 标题位置一致
  • 内容对齐规范
  • 项目符号与文本无截断
  • 图表适配幻灯片边界
  • 标题与标签可见且可读
内容质量：
  • 每张幻灯片一个核心观点（不过载）
  • 文本极少（最多3-6个项目符号）
  • 项目符号简洁（每个5-7个单词）
  • 图表简化清晰（非直接复制论文图表）
  • 数据可视化标签大且可读
  • 引用存在且格式规范
  • 结果/数据幻灯片占主导（40-50%内容）
结构与流程：
  • 叙事清晰（引言→方法→结果→讨论）
  • 幻灯片间逻辑连贯
  • 幻灯片数量与演讲时长匹配（约每分钟1张）
  • 标题幻灯片包含作者、机构、日期
  • 引言引用相关背景文献（3-5篇）
  • 讨论引用对比文献（3-5篇）
  • 结论幻灯片总结关键发现
  • 末尾有致谢/资金幻灯片
科学内容：
  • 研究问题清晰陈述
  • 方法总结充分（不过度详细）
  • 结果呈现逻辑清晰且可视化效果好
  • 统计显著性标注恰当
  • 结论有展示的数据支持
  • 适当承认局限性
  • 讨论未来方向或更广泛影响
需标记的常见演示文稿问题：
严重问题（必须修复）：
  • 文本溢出导致内容不可读
  • 字体过小（<18pt）
  • 元素重叠遮挡数据
  • 对比度不足（文本难以阅读）
  • 图表过于复杂或难以辨认
  • 无引用（完全无依据的主张）
  • 幻灯片数量与时长严重不匹配
主要问题（应修复）：
  • 幻灯片间设计不一致
  • 文本过多（大段文字而非项目符号）
  • 图表简化不佳（坐标轴标签过小）
  • 布局拥挤留白不足
  • 缺少关键结构元素（无结论幻灯片）
  • 配色不当（非色盲友好）
  • 结果内容占比低（<30%幻灯片）
次要问题（改进建议）：
  • 可增加更多可视化/图表
  • 部分幻灯片文本略多
  • 轻微对齐不一致
  • 可增加更多留白
  • 添加更多引用可强化主张
  • 配色方案可更现代

Review Report Format for Presentations

演示文稿评审报告格式

Summary Statement:
  • Overall impression of presentation quality
  • Appropriateness for target audience and duration
  • Key strengths (visual design, content, clarity)
  • Key weaknesses (formatting issues, content gaps)
  • Recommendation (ready to present, minor revisions, major revisions)
Layout and Formatting Issues (By Slide Number):
Slide 3: Text overflow - bullet point 4 extends beyond right margin
Slide 7: Element overlap - figure overlaps with caption text
Slide 12: Font size - axis labels too small to read from distance
Slide 18: Alignment - title not centered
Content and Structure Feedback:
  • Adequacy of background context and citations
  • Clarity of research question and objectives
  • Quality of methods summary
  • Effectiveness of results presentation
  • Strength of conclusions and implications
Design and Accessibility:
  • Overall visual appeal and professionalism
  • Color contrast and readability
  • Colorblind accessibility
  • Consistency across slides
Timing and Scope:
  • Whether slide count matches intended duration
  • Appropriate level of detail for talk type
  • Balance between sections
总结陈述：
  • 演示文稿质量的整体印象
  • 对目标受众与时长的适配性
  • 核心优势（视觉设计、内容、清晰度）
  • 核心劣势（格式问题、内容缺口）
  • 建议（可直接展示、小修、大修）
布局与格式问题（按幻灯片编号）：
Slide 3: Text overflow - bullet point 4 extends beyond right margin
Slide 7: Element overlap - figure overlaps with caption text
Slide 12: Font size - axis labels too small to read from distance
Slide 18: Alignment - title not centered
内容与结构反馈：
  • 背景信息与引用的充分性
  • 研究问题与目标的清晰度
  • 方法总结的质量
  • 结果呈现的有效性
  • 结论与意义的说服力
设计与可访问性：
  • 整体视觉吸引力与专业性
  • 颜色对比度与可读性
  • 色盲可访问性
  • 幻灯片间一致性
时长与范围：
  • 幻灯片数量是否与预期时长匹配
  • 细节程度是否适合演讲类型
  • 各部分平衡情况

Example Image-Based Review Process

基于图像的评审流程示例

[14:30:00] PEER REVIEW: Starting review of presentation
[14:30:05] PEER REVIEW: Presentation detected - converting to images
[14:30:10] PDF REVIEW: Running pdf_to_images.py on presentation.pdf
[14:30:15] PDF REVIEW: Converted 25 slides to images in review/ directory
[14:30:20] PDF REVIEW: Inspecting slide 1/25 - title slide
[14:30:25] PDF REVIEW: Inspecting slide 2/25 - introduction
...
[14:35:40] PDF REVIEW: Inspecting slide 25/25 - acknowledgments
[14:35:45] PDF REVIEW: Completed image-based review
[14:35:50] PEER REVIEW: Found 8 layout issues, 3 content issues
[14:35:55] PEER REVIEW: Generating structured feedback by slide number
Remember: For presentations, the visual inspection via images is MANDATORY. Never attempt to read presentation PDFs as text - it will fail and miss all visual formatting issues.
[14:30:00] PEER REVIEW: Starting review of presentation
[14:30:05] PEER REVIEW: Presentation detected - converting to images
[14:30:10] PDF REVIEW: Running pdf_to_images.py on presentation.pdf
[14:30:15] PDF REVIEW: Converted 25 slides to images in review/ directory
[14:30:20] PDF REVIEW: Inspecting slide 1/25 - title slide
[14:30:25] PDF REVIEW: Inspecting slide 2/25 - introduction
...
[14:35:40] PDF REVIEW: Inspecting slide 25/25 - acknowledgments
[14:35:45] PDF REVIEW: Completed image-based review
[14:35:50] PEER REVIEW: Found 8 layout issues, 3 content issues
[14:35:55] PEER REVIEW: Generating structured feedback by slide number
切记： 对于演示文稿，必须通过图像进行视觉检查。切勿直接读取演示文稿PDF文本 - 这会失败且遗漏所有视觉格式问题。

Resources

资源

This skill includes reference materials to support comprehensive peer review:
此技能包含支持全面同行评审的参考资料：

references/reporting_standards.md

references/reporting_standards.md

Guidelines for major reporting standards across disciplines (CONSORT, PRISMA, ARRIVE, MIAME, STROBE, etc.) to evaluate completeness of methods and results reporting.
跨学科主要报告标准指南（CONSORT、PRISMA、ARRIVE等），用于评估方法与结果报告的完整性。

references/common_issues.md

references/common_issues.md

Catalog of frequent methodological and statistical issues encountered in peer review, with guidance on identifying and addressing them.
同行评审中常见的方法论与统计问题目录，包含识别与解决这些问题的指导。

Final Checklist

最终检查清单

Before finalizing the review, verify:
  • Summary statement clearly conveys overall assessment
  • Major concerns are clearly identified and justified
  • Suggested revisions are specific and actionable
  • Minor issues are noted but properly categorized
  • Statistical methods have been evaluated
  • Reproducibility and data availability assessed
  • Ethical considerations verified
  • Figures and tables evaluated for quality and integrity
  • Writing quality assessed
  • Tone is constructive and professional throughout
  • Review is thorough but proportionate to manuscript scope
  • Recommendation is consistent with identified issues
完成评审前，验证：
  • 总结陈述清晰传达整体评估
  • 核心问题已明确识别并论证
  • 建议的修改具体且可操作
  • 次要问题已记录并正确分类
  • 统计方法已评估
  • 可重复性与数据可用性已评估
  • 伦理考量已验证
  • 图表与表格已评估质量与完整性
  • 写作质量已评估
  • 全程语气建设性且专业
  • 评审全面且与手稿范围相称
  • 建议与识别的问题一致