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Scientific Hypothesis Generation

科学假设生成

Overview

概述

Hypothesis generation is a systematic process for developing testable explanations. Formulate evidence-based hypotheses from observations, design experiments, explore competing explanations, and develop predictions. Apply this skill for scientific inquiry across domains.
假设生成是开发可验证解释的系统化流程。基于观察构建有证据支撑的假设、设计实验、探索竞争性解释并制定预测。将此方法应用于各领域的科学研究。

When to Use This Skill

何时使用该方法

This skill should be used when:
  • Developing hypotheses from observations or preliminary data
  • Designing experiments to test scientific questions
  • Exploring competing explanations for phenomena
  • Formulating testable predictions for research
  • Conducting literature-based hypothesis generation
  • Planning mechanistic studies across scientific domains
在以下场景中应使用该方法：
  • 基于观察或初步数据开发假设
  • 设计实验以验证科学问题
  • 探索现象的竞争性解释
  • 为研究制定可验证的预测
  • 基于文献研究生成假设
  • 规划跨科学领域的机制研究

Visual Enhancement with Scientific Schematics

借助科研示意图优化可视化效果

⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:
  1. Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations)
  2. Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree)
How to generate figures:
  • 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
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:
  • Hypothesis framework diagrams showing competing explanations
  • Experimental design flowcharts
  • Mechanistic pathway diagrams
  • Prediction decision trees
  • Causal relationship diagrams
  • Theoretical model visualizations
  • Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
⚠️ 强制要求：每份假设生成报告必须包含至少1-2张使用scientific-schematics工具生成的AI示意图。
此要求为强制性，无可视化元素的假设报告视为不完整。在最终确定任何文档前：
  1. 至少生成一张示意图或图表（例如，展示竞争性解释的假设框架图）
  2. 综合性报告建议生成2-3张图（机制通路图、实验设计流程图、预测决策树）
如何生成图表：
  • 使用scientific-schematics工具生成符合出版级质量的AI驱动图表
  • 只需用自然语言描述你想要的图表
  • Nano Banana Pro会自动生成、审核并优化示意图
生成示意图的命令：
bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
AI会自动：
  • 创建格式规范的出版级图片
  • 通过多轮迭代进行审核和优化
  • 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：
  • 展示竞争性解释的假设框架图
  • 实验设计流程图
  • 机制通路图
  • 预测决策树
  • 因果关系图
  • 理论模型可视化
  • 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工具的文档。

Workflow

工作流程

Follow this systematic process to generate robust scientific hypotheses:
遵循以下系统化流程生成严谨的科学假设：

1. Understand the Phenomenon

1. 理解研究现象

Start by clarifying the observation, question, or phenomenon that requires explanation:
  • Identify the core observation or pattern that needs explanation
  • Define the scope and boundaries of the phenomenon
  • Note any constraints or specific contexts
  • Clarify what is already known vs. what is uncertain
  • Identify the relevant scientific domain(s)
首先明确需要解释的观察结果、问题或现象：
  • 确定需要解释的核心观察结果或模式
  • 定义现象的范围和边界
  • 记录任何约束条件或特定背景
  • 明确已知信息与未知信息
  • 确定相关的科学领域

2. Conduct Comprehensive Literature Search

2. 开展全面的文献检索

Search existing scientific literature to ground hypotheses in current evidence. Use both PubMed (for biomedical topics) and general web search (for broader scientific domains):
For biomedical topics:
  • Use WebFetch with PubMed URLs to access relevant literature
  • Search for recent reviews, meta-analyses, and primary research
  • Look for similar phenomena, related mechanisms, or analogous systems
For all scientific domains:
  • Use WebSearch to find recent papers, preprints, and reviews
  • Search for established theories, mechanisms, or frameworks
  • Identify gaps in current understanding
Search strategy:
  • Begin with broad searches to understand the landscape
  • Narrow to specific mechanisms, pathways, or theories
  • Look for contradictory findings or unresolved debates
  • Consult 
    references/literature_search_strategies.md
    for detailed search techniques
检索现有科学文献，让假设建立在当前证据的基础上。针对生物医学主题使用PubMed，针对更广泛的科学领域使用通用网络检索：
针对生物医学主题：
  • 使用WebFetch工具获取PubMed链接的相关文献
  • 检索近期综述、荟萃分析和原始研究
  • 寻找类似现象、相关机制或类比系统
针对所有科学领域：
  • 使用WebSearch工具查找近期论文、预印本和综述
  • 检索已确立的理论、机制或框架
  • 识别当前研究中的空白
检索策略：
  • 从宽泛检索开始，了解研究领域全貌
  • 逐步缩小到特定机制、通路或理论
  • 寻找矛盾的研究结果或未解决的争议
  • 参考
    references/literature_search_strategies.md
    获取详细的检索技巧

3. Synthesize Existing Evidence

3. 整合现有证据

Analyze and integrate findings from literature search:
  • Summarize current understanding of the phenomenon
  • Identify established mechanisms or theories that may apply
  • Note conflicting evidence or alternative viewpoints
  • Recognize gaps, limitations, or unanswered questions
  • Identify analogies from related systems or domains
分析并整合文献检索的结果：
  • 总结对该现象的当前认知
  • 识别可能适用的已确立机制或理论
  • 记录矛盾证据或替代观点
  • 认识到研究空白、局限性或未解决的问题
  • 识别相关系统或领域中的类比

4. Generate Competing Hypotheses

4. 生成竞争性假设

Develop 3-5 distinct hypotheses that could explain the phenomenon. Each hypothesis should:
  • Provide a mechanistic explanation (not just description)
  • Be distinguishable from other hypotheses
  • Draw on evidence from the literature synthesis
  • Consider different levels of explanation (molecular, cellular, systemic, population, etc.)
Strategies for generating hypotheses:
  • Apply known mechanisms from analogous systems
  • Consider multiple causative pathways
  • Explore different scales of explanation
  • Question assumptions in existing explanations
  • Combine mechanisms in novel ways
开发3-5种可解释该现象的不同假设。每个假设应：
  • 提供机制性解释（而非仅描述）
  • 与其他假设可区分
  • 基于文献整合的证据
  • 考虑不同层面的解释（分子、细胞、系统、种群等）
生成假设的策略：
  • 应用类比系统中的已知机制
  • 考虑多种致病通路
  • 探索不同尺度的解释
  • 质疑现有解释中的假设
  • 以新颖的方式组合机制

5. Evaluate Hypothesis Quality

5. 评估假设质量

Assess each hypothesis against established quality criteria from 
references/hypothesis_quality_criteria.md
:
Testability: Can the hypothesis be empirically tested? Falsifiability: What observations would disprove it? Parsimony: Is it the simplest explanation that fits the evidence? Explanatory Power: How much of the phenomenon does it explain? Scope: What range of observations does it cover? Consistency: Does it align with established principles? Novelty: Does it offer new insights beyond existing explanations?
Explicitly note the strengths and weaknesses of each hypothesis.
参考
references/hypothesis_quality_criteria.md
中的既定标准评估每个假设：
可验证性： 该假设能否通过实证测试？ 可证伪性： 哪些观察结果可以推翻该假设？ 简洁性： 它是否是符合证据的最简解释？ 解释力： 它能解释多少现象？ 适用范围： 它涵盖哪些范围的观察结果？ 一致性： 它是否与已确立的原理一致？ 创新性： 它是否能提供超越现有解释的新见解？
明确记录每个假设的优势和劣势。

6. Design Experimental Tests

6. 设计实验测试方案

For each viable hypothesis, propose specific experiments or studies to test it. Consult 
references/experimental_design_patterns.md
for common approaches:
Experimental design elements:
  • What would be measured or observed?
  • What comparisons or controls are needed?
  • What methods or techniques would be used?
  • What sample sizes or statistical approaches are appropriate?
  • What are potential confounds and how to address them?
Consider multiple approaches:
  • Laboratory experiments (in vitro, in vivo, computational)
  • Observational studies (cross-sectional, longitudinal, case-control)
  • Clinical trials (if applicable)
  • Natural experiments or quasi-experimental designs
针对每个可行的假设，提出具体的实验或研究方案来测试它。参考
references/experimental_design_patterns.md
获取常见方法：
实验设计要素：
  • 要测量或观察什么？
  • 需要哪些对照或比较？
  • 将使用哪些方法或技术？
  • 样本量或统计方法是否合适？
  • 潜在的混杂因素有哪些，如何解决？
考虑多种方法：
  • 实验室实验（体外、体内、计算模拟）
  • 观察性研究（横断面、纵向、病例对照）
  • 临床试验（如适用）
  • 自然实验或准实验设计

7. Formulate Testable Predictions

7. 制定可验证的预测

For each hypothesis, generate specific, quantitative predictions:
  • State what should be observed if the hypothesis is correct
  • Specify expected direction and magnitude of effects when possible
  • Identify conditions under which predictions should hold
  • Distinguish predictions between competing hypotheses
  • Note predictions that would falsify the hypothesis
针对每个假设，生成具体的、可量化的预测：
  • 说明如果假设成立，应观察到什么结果
  • 尽可能明确预期效应的方向和幅度
  • 确定预测成立的条件
  • 区分不同竞争性假设的预测结果
  • 记录可证伪该假设的预测

8. Present Structured Output

8. 生成结构化输出

Generate a professional LaTeX document using the template in 
assets/hypothesis_report_template.tex
. The report should be well-formatted with colored boxes for visual organization and divided into a concise main text with comprehensive appendices.
Document Structure:
Main Text (Maximum 4 pages):
  1. Executive Summary - Brief overview in summary box (0.5-1 page)
  2. Competing Hypotheses - Each hypothesis in its own colored box with brief mechanistic explanation and key evidence (2-2.5 pages for 3-5 hypotheses)
    • IMPORTANT: Use 
      \newpage
      before each hypothesis box to prevent content overflow
    • Each box should be ≤0.6 pages maximum
  3. Testable Predictions - Key predictions in amber boxes (0.5-1 page)
  4. Critical Comparisons - Priority comparison boxes (0.5-1 page)
Keep main text highly concise - only the most essential information. All details go to appendices.
Page Break Strategy:
  • Always use 
    \newpage
    before hypothesis boxes to ensure they start on fresh pages
  • This prevents content from overflowing off page boundaries
  • LaTeX boxes (tcolorbox) do not automatically break across pages
Appendices (Comprehensive, Detailed):
  • Appendix A: Comprehensive literature review with extensive citations
  • Appendix B: Detailed experimental designs with full protocols
  • Appendix C: Quality assessment tables and detailed evaluations
  • Appendix D: Supplementary evidence and analogous systems
Colored Box Usage:
Use the custom box environments from 
hypothesis_generation.sty
:
  • hypothesisbox1
    through 
    hypothesisbox5
    - For each competing hypothesis (blue, green, purple, teal, orange)
  • predictionbox
    - For testable predictions (amber)
  • comparisonbox
    - For critical comparisons (steel gray)
  • evidencebox
    - For supporting evidence highlights (light blue)
  • summarybox
    - For executive summary (blue)
Each hypothesis box should contain (keep concise for 4-page limit):
  • Mechanistic Explanation: 1-2 brief paragraphs (6-10 sentences max) explaining HOW and WHY
  • Key Supporting Evidence: 2-3 bullet points with citations (most important evidence only)
  • Core Assumptions: 1-2 critical assumptions
All detailed explanations, additional evidence, and comprehensive discussions belong in the appendices.
Critical Overflow Prevention:
  • Insert 
    \newpage
    before each hypothesis box to start it on a fresh page
  • Keep each complete hypothesis box to ≤0.6 pages (approximately 15-20 lines of content)
  • If content exceeds this, move additional details to Appendix A
  • Never let boxes overflow off page boundaries - this creates unreadable PDFs
Citation Requirements:
Aim for extensive citation to support all claims:
  • Main text: 10-15 key citations for most important evidence only (keep concise for 4-page limit)
  • Appendix A: 40-70+ comprehensive citations covering all relevant literature
  • Total target: 50+ references in bibliography
Main text citations should be selective - cite only the most critical papers. All comprehensive citation and detailed literature discussion belongs in the appendices. Use 
\citep{author2023}
for parenthetical citations.
LaTeX Compilation:
The template requires XeLaTeX or LuaLaTeX for proper rendering:
bash
xelatex hypothesis_report.tex
bibtex hypothesis_report
xelatex hypothesis_report.tex
xelatex hypothesis_report.tex
Required packages: The 
hypothesis_generation.sty
style package must be in the same directory or LaTeX path. It requires: tcolorbox, xcolor, fontspec, fancyhdr, titlesec, enumitem, booktabs, natbib.
Page Overflow Prevention:
To prevent content from overflowing on pages, follow these critical guidelines:
  1. Monitor Box Content Length: Each hypothesis box should fit comfortably on a single page. If content exceeds ~0.7 pages, it will likely overflow.
  2. Use Strategic Page Breaks: Insert 
    \newpage
    before boxes that contain substantial content:
    latex
    \newpage
\begin{hypothesisbox1}[Hypothesis 1: Title]
% Long content here
\end{hypothesisbox1}
  3. Keep Main Text Boxes Concise: For the 4-page main text limit:
    • Each hypothesis box: Maximum 0.5-0.6 pages
    • Mechanistic explanation: 1-2 brief paragraphs only (6-10 sentences max)
    • Key evidence: 2-3 bullet points only
    • Core assumptions: 1-2 items only
    • If content is longer, move details to appendices
  4. Break Long Content: If a hypothesis requires extensive explanation, split across main text and appendix:
    • Main text box: Brief mechanistic overview + 2-3 key evidence points
    • Appendix A: Detailed mechanism explanation, comprehensive evidence, extended discussion
  5. Test Page Boundaries: Before each new box, consider if remaining page space is sufficient. If less than 0.6 pages remain, use 
    \newpage
    to start the box on a fresh page.
  6. Appendix Page Management: In appendices, use 
    \newpage
    between major sections to avoid overflow in detailed content areas.
Quick Reference: See 
assets/FORMATTING_GUIDE.md
for detailed examples of all box types, color schemes, and common formatting patterns.
使用
assets/hypothesis_report_template.tex
中的模板生成专业的LaTeX文档。报告格式应清晰，使用彩色框进行视觉组织，分为简洁的正文和详尽的附录。
文档结构：
正文（最多4页）：
  1. 执行摘要 - 摘要框中的简要概述（0.5-1页）
  2. 竞争性假设 - 每个假设放在单独的彩色框中，包含简要的机制解释和关键证据（3-5个假设占2-2.5页）
    • 重要提示： 在每个假设框前使用
      \newpage
      ，防止内容溢出
    • 每个框最多≤0.6页
  3. 可验证预测 - 关键预测放在琥珀色框中（0.5-1页）
  4. 关键比较 - 优先级比较框（0.5-1页）
正文需高度简洁 - 仅保留最关键的信息。所有细节放入附录。
分页策略：
  • 始终在假设框前使用
    \newpage
    ，确保它们从新页面开始
  • 这可防止内容溢出页面边界
  • LaTeX框（tcolorbox）不会自动跨页拆分
附录（详尽、详细）：
  • 附录A： 包含大量引用的全面文献综述
  • 附录B： 包含完整方案的详细实验设计
  • 附录C： 质量评估表和详细评估
  • 附录D： 补充证据和类比系统
彩色框使用：
使用
hypothesis_generation.sty
中的自定义框环境：
  • hypothesisbox1
    至
    hypothesisbox5
    - 用于每个竞争性假设（蓝色、绿色、紫色、蓝绿色、橙色）
  • predictionbox
    - 用于可验证预测（琥珀色）
  • comparisonbox
    - 用于关键比较（钢灰色）
  • evidencebox
    - 用于支持性证据高亮（浅蓝色）
  • summarybox
    - 用于执行摘要（蓝色）
每个假设框应包含（为4页限制保持简洁）：
  • 机制解释： 1-2段简要说明（最多6-10句话）
  • 关键支持证据： 2-3个带引用的要点（仅保留最重要的证据）
  • 核心假设： 1-2个关键假设
所有详细解释、额外证据和全面讨论均放入附录。
页面溢出预防：
为防止内容溢出页面，遵循以下关键指南：
  1. 监控框内容长度： 每个假设框应能舒适地放在单个页面上。如果内容超过约0.7页，很可能会溢出。
  2. 使用战略性分页： 在包含大量内容的框前插入
    \newpage
    ：
    latex
    \newpage
\begin{hypothesisbox1}[Hypothesis 1: Title]
% 长内容放在这里
\end{hypothesisbox1}
  3. 保持正文框简洁： 针对4页正文限制：
    • 每个假设框：最多0.5-0.6页
    • 机制解释：仅1-2段简要说明（最多6-10句话）
    • 关键证据：仅2-3个要点
    • 核心假设：仅1-2项
    • 如果内容过长，将细节移至附录
  4. 拆分长内容： 如果某个假设需要大量解释，将其拆分为正文和附录两部分：
    • 正文框：简要机制概述 + 2-3个关键证据点
    • 附录A：详细机制解释、全面证据、扩展讨论
  5. 测试页面边界： 在每个新框前，考虑剩余页面空间是否足够。如果剩余空间少于0.6页，使用
    \newpage
    让框从新页面开始。
  6. 附录页面管理： 在附录中，主要部分之间使用
    \newpage
    ，避免详细内容区域溢出。
快速参考： 参考
assets/FORMATTING_GUIDE.md
获取所有框类型、配色方案和常见格式模式的详细示例。

Quality Standards

质量标准

Ensure all generated hypotheses meet these standards:
  • Evidence-based: Grounded in existing literature with citations
  • Testable: Include specific, measurable predictions
  • Mechanistic: Explain how/why, not just what
  • Comprehensive: Consider alternative explanations
  • Rigorous: Include experimental designs to test predictions
确保所有生成的假设符合以下标准：
  • 基于证据： 以现有文献为基础并带有引用
  • 可验证： 包含具体、可测量的预测
  • 机制性： 解释如何/为什么，而非仅是什么
  • 全面性： 考虑替代解释
  • 严谨性： 包含测试预测的实验设计

Resources

资源

references/

references/

  • hypothesis_quality_criteria.md
    - Framework for evaluating hypothesis quality (testability, falsifiability, parsimony, explanatory power, scope, consistency)
  • experimental_design_patterns.md
    - Common experimental approaches across domains (RCTs, observational studies, lab experiments, computational models)
  • literature_search_strategies.md
    - Effective search techniques for PubMed and general scientific sources
  • hypothesis_quality_criteria.md
    - 评估假设质量的框架（可验证性、可证伪性、简洁性、解释力、适用范围、一致性）
  • experimental_design_patterns.md
    - 跨领域的常见实验方法（随机对照试验、观察性研究、实验室实验、计算模型）
  • literature_search_strategies.md
    - 针对PubMed和通用科学来源的有效检索技巧

assets/

assets/

  • hypothesis_generation.sty
    - LaTeX style package providing colored boxes, professional formatting, and custom environments for hypothesis reports
  • hypothesis_report_template.tex
    - Complete LaTeX template with main text structure and comprehensive appendix sections
  • FORMATTING_GUIDE.md
    - Quick reference guide with examples of all box types, color schemes, citation practices, and troubleshooting tips
  • hypothesis_generation.sty
    - LaTeX样式包，为假设报告提供彩色框、专业格式和自定义环境
  • hypothesis_report_template.tex
    - 完整的LaTeX模板，包含正文结构和全面的附录部分
  • FORMATTING_GUIDE.md
    - 快速参考指南，包含所有框类型、配色方案、引用规范和故障排除技巧的示例