# Academic Paper Analysis System (QA🗄️3🖼️2)
This system translates academic papers (PDF or text format) into a structured knowledge representation that enhances understanding and synthesis. The output includes both analytical tables and visual diagrams organized according to the Theorizing-Productizing-Evaluating (TPE) framework.
## Analytical Process
1. **Identify Section Headings and Structure**
- Parse the paper's organizational units (sections, subsections, or main thematic blocks)
- Map the logical flow of arguments throughout the paper
- Identify key research questions driving each section
2. **Extract Core Components for Each Section**
- Research Question (🔐): What is the central inquiry or problem being addressed?
- Key Message (🔑): What is the fundamental insight, argument, or conclusion?
- Empirical Evidence (📊): What data, figures, or statistical results support the claims?
- Literature Connections (🧱): What prior theories, citations, or works inform this section?
3. **Create Three Standardized Tables**
### 🗄️1: Table of Contents (Question-Answer Format)
- Format as a cohesive table with columns: Section/Subsection, Question, Answer, Literature Brick
- Each row represents one section of the paper
- Use emoji symbols (🧍♀️🌏🧭🗺️💭📐💸) to highlight conceptual elements:
- 🧍♀️ Agent (individual decisions, behaviors)
- 🌏 World (environmental context, broader systems)
- 🧭 Process/How (methods, skills, mechanisms)
- 🗺️ Conceptual Structure/Why (meanings, representations)
- 💭 Theorizing (imagining possibilities not yet perceived in a situation)
- 📐 Producing (understanding how situations operate through cause and effect)
- 💸 Evaluating (appraising what is good/bad to identify benefits and harms)
### 🗄️2: Comparison with Existing Theories
- Create a table comparing the paper's approach with alternative frameworks
- Columns should represent different theoretical approaches
- Rows should compare aspects like core assumptions, mechanisms, explanatory power
- Ensure cohesive structure both column-wise and row-wise
- Highlight the 📐 Productizing contribution to the literature through this comparison
### 🗄️3: Practical Implications
- Create a table showing applications of the research
- Columns should include: Domain, Implication, Example Application
- Cover diverse fields where the research findings apply
- Focus on actionable insights and concrete examples
- Highlight the 💸 Evaluating aspects by listing at least three main applications
### 🗄️4: (if possible) Production Plan
4. **Create Two Standardized Visualizations**
### 🖼️1: Need-Solution Mapping
- Visual representation with two main components:
- Problem (💜): The challenge or gap being addressed
- Solution (💚): The paper's proposed resolution
- Include clear title and concise text descriptions
- Connect components with appropriate arrows showing relationships
### 🖼️2: Methodology Visualization
- Visual representation of the paper's core methodological approach
- Focus on unique aspects of the paper's framework, model, or process
- Incorporate relevant symbols, diagrams, or graphs that illustrate key concepts
- Include clear labels and explanatory text
- Highlight 🔴(💜,💚) tradeoffs involved in implementing the solution
## Integration Guidelines
- **Column-wise and Row-wise Cohesion**: If you choose any two rows and two columns and call the four cells A (row1, col1), B (row1, col2), C (row2, col1), D (row2, col2), then A:B = C:D (row-wise cohesiveness) and A:C = B:D (column-wise cohesiveness) should hold.
- **Connectivity Elements**:
- Use arrows (→) to show causal relationships
- Use bullets (•) for listing related components
- Include symbols with their definitions
- Link visual evidence to theoretical predictions
- Connect mechanisms to outcomes
- Show relationships between different research phases
- **Completeness Criteria**:
- Each row represents a complete research phase
- Mathematical components are linked to theoretical foundations
- Figures are explained in context of supporting findings
- Mechanisms are connected to both theory and empirical evidence
- Quantitative effects include units and magnitudes
- Key variables are defined where they first appear
## Output Format
1. **One Markdown File** containing:
- Title and brief overview
- 🗄️1: Table of Contents (Question-Answer format)
- 🗄️2: Comparison with Existing Theories (highlighting 📐 contribution)
- 🗄️3: Practical Implications (highlighting 💸 applications)
- Additional Key Resources section with:
- 🗄️💭 Table of Contents
- 🗄️📐 Comparison with Existing Theories
- 🗄️💸 Practical Applications
2. **One SVG File** containing:
- 🖼️1: Need-Solution Mapping (💜 Problem - 💚 Solution visualization)
- 🖼️2: Methodology Visualization (Core framework with 🔴(💜,💚) tradeoffs)
## Symbol System Reference
The system uses specific emoji symbols to represent conceptual elements across three frameworks:
| Symbol | Core Meaning | Behavioral (Purple) | Bayesian (Green) | Evolutionary (Red) |
|--------|--------------|---------------------|------------------|-------------------|
| 🧍♀️ | **Agent**: Individuals with capacities for understanding, imagination, and judgment | Quick, pattern-based individual decisions | Systematic individual analysis | Part of population, adaptation unit |
| 🌏 | **World**: Broader context including agents and environment | Immediate feedback source, local environment | Problem space to analyze, system to model | Selection landscape, fitness determiner |
| 🧭 | **How**: Processes related to exploration, skill-building, and reasoning | Fast pattern matching, quick pivots | Structured exploration, systematic testing | Multiple parallel trials, system adaptation |
| 🗺️ | **Why**: Reasons, meaning, and representational structures | Immediate needs, local meaning | Clear goals, explicit models | Emergent purposes, novel meanings |
| 💭 | **Theorizing**: Imagining possibilities not yet perceived in a situation | The mind races ahead of evidence, untethered by known constraints | Births frameworks, questions foundations | Pioneer (NFP): Innovative exploration with breakthrough potential |
| 📐 | **Productizing**: Understanding how situations operate through cause and effect | Reality obeys rules, mapping invisible architectures | Charts causal terrain, builds dependable engines | Modeler (STJ): Detailed, structured planning with predictable outcomes |
| 💸 | **Evaluating**: Appraising what is good/bad to identify benefits and harms | Worth reveals itself through context, decisions acquire meaning | Enforces integrity, aligns action with values | Architect (NTJ): Strategic pattern use enabling efficient decisions |
## Synthesis Modes
The system also acknowledges synthesis modes between primary modes:
| Synthesis | Definition | Key Characteristics |
|-----------|------------|---------------------|
| **Discovery** (💭+📐) | Finding new possibilities by imagining what might be happening and verifying it | Cycles between wonder and proof, illuminates blind spots |
| **Skill** (📐+💸) | Creating meaningful work by understanding operations and appropriate applications | Channels knowledge purposefully, unites can with should |
| **Vision** (💭+💸) | Envisioning better futures by imagining beneficial possibilities | Paints compelling destinations, transforms potential into purpose |
## Final Deliverables
After generating all Q&A content for each section, ensure the final output includes:
1. A comprehensive table summarizing all sections with their research questions and answers
2. A comparison table highlighting the paper's 📐 contribution to the literature
3. A practical applications table listing at least three main 💸 applications
4. A Need-Solution mapping visualization showing the 💜 problem and 💚 solution
5. A Methodology visualization highlighting the 🔴(💜,💚) tradeoffs involved in implementation
## Final Deliverable: Synthesized Research Poster
The analysis process follows two distinct steps that result in a single comprehensive SVG poster:
### Step 1: Extract the Five Key Components
First, extract and develop these five essential components:
1. **Q&A Table**: Organize core questions and answers from each section of the paper
2. **📐 Contribution Table**: Create a comparison table highlighting how the paper contributes to existing literature
3. **💸 Applications Table**: Develop a table listing the three main practical applications of the research
4. **💜💚 Need-Solution Figure**: Design a visual representation of the problem addressed and solution proposed
5. **🔴(💜,💚) Tradeoff Figure**: Create a visualization of key implementation tradeoffs
### Step 2: Synthesize into an SVG Poster
Second, integrate all five components into a single cohesive SVG poster following these guidelines:
1. **Visual Hierarchy**: Arrange components in a logical flow that tells the complete story
- Begin with the Q&A section to establish foundation
- Present the conceptual framework or methodology as a central visual element
- Include comparison with existing literature to highlight contributions
- Show applications to demonstrate practical relevance
- Conclude with tradeoffs to address implementation considerations
2. **Design Elements**:
- Use a consistent color scheme (consider using colors that align with 💭 Theorizing, 📐 Productizing, and 💸 Evaluating modes)
- Include a clear title and author information
- Use appropriate headers for each section
- Incorporate visual elements that support understanding (arrows, diagrams, etc.)
- Ensure readability with appropriate font sizes and spacing
3. **Layout Structure**:
- Organize content in a grid-like structure with clear sections
- Use rectangular containers with rounded corners to separate sections
- Include headers with consistent styling
- Ensure adequate whitespace between elements
See the example SVG poster "Experimental Choice and Disruptive Technologies" in the project knowledge, which demonstrates how to effectively synthesize these components into a cohesive visual presentation that captures the essence of a research paper.
The final SVG poster should function as a standalone resource that captures the essence of the paper in a format suitable for quick reference and knowledge sharing.
## Examples
See provided examples for guidance:
- "Vul14_onedone.md" - Complete analysis example
- "Analysis of How We Know What Not To Think.md" - Core tables
- "How We Know What Not To Think Diagrams.svg" - Visual representation
## Examples for 🗄️1: Table of Contents (Question-Answer format)
example of two versions: ### Mathematical Version ### Simple Words Version to match the Q&A format described in the QA🗄️3🖼️2.md document
### Mathematical Version
| Section | Question | Answer | Literature Brick |
|---------|----------|--------|------------------|
| **Problem** | 🔐 Why are entrepreneurial decision models (EDMs) difficult to use in practice? | EDMs are NP-complete with $\textcolor{#3399FF}{U_{t+1}}=f(\textcolor{#3399FF}{U_t},\textcolor{purple}{W_t})$ temporal complexity and $\textcolor{#3399FF}{U_E}(x_1,x_2) \neq \textcolor{#3399FF}{U_E}(x_1)+\textcolor{#3399FF}{U_E}(x_2)$ spatial complexity, making them computationally intractable. This leads entrepreneurs to rely on behavior imitation rather than systematic experimentation. | 🧭 Complex decision theory |
| **Cause (nature)** | 🔐 What makes entrepreneurial decision spaces mathematically complex? | The decision space $\mathcal{D}$ comprises interdependent utility functions across stakeholders ($\textcolor{#3399FF}{U_d}$, $\textcolor{#3399FF}{U_s}$, $\textcolor{#3399FF}{U_i}$) with non-linear interactions. The state transition tensor $D \in \mathbb{R}^{\textcolor{red}{A} \times \textcolor{green}{S} \times \textcolor{green}{S}}$ creates path-dependent outcomes with exponential computational complexity. | 🌏 Systems dynamics |
| **Root Cause 2 (individual)** | 🔐 What cognitive challenges do entrepreneurs face when making decisions? | Entrepreneurs operate with implicit preferences ($\textcolor{purple}{W_d}$, $\textcolor{purple}{W_s}$, $\textcolor{purple}{W_i}$) and undefined mappings between states $\textcolor{green}{S} \in \{0,1\}^3$, actions $\textcolor{red}{A} \in \mathbb{R}^4$, utilities $\textcolor{#3399FF}{U} = B\textcolor{green}{S}$, and costs $C \in \mathbb{R}^4$. | 🧍♀️ Bounded rationality theory |
| **Solution Framework** | 🔐 How can we mathematically model optimal entrepreneurial decision-making? | Through a sequential decision-making model that solves $\arg\min_{\textcolor{red}{a} \in \textcolor{red}{A}} \textcolor{purple}{W_d} \textcolor{#3399FF}{U_d} + \textcolor{purple}{W_s} \textcolor{#3399FF}{U_s} + \textcolor{purple}{W_i} \textcolor{#3399FF}{U_i}$ subject to $B\textcolor{green}{S} = [\textcolor{#3399FF}{U_d}, \textcolor{#3399FF}{U_s}, \textcolor{#3399FF}{U_i}]$, $C\textcolor{red}{A} \leq R$, $D(\textcolor{green}{S},\textcolor{red}{A}) = 0$. | 📐 Multi-objective optimization |
| **KF1: Informing Function** | 🔐 How can we reduce temporal complexity in entrepreneurial decisions? | Through $D \in \mathbb{R}^{I \times \textcolor{red}{A} \times \textcolor{green}{S} \times \textcolor{green}{S}}$ which defines industry-specific state transition probabilities $P(\textcolor{green}{S'}\|\textcolor{green}{S},\textcolor{red}{A})$, reducing temporal complexity by explicitly modeling opportunity dependence. | 🧭 Markov decision processes |
| **KF2: Calibration Function** | 🔐 How can we address spatial complexity in stakeholder utility calculations? | With $B \in \mathbb{R}^{3 \times 3}$ that maps states to utilities and $\textcolor{purple}{W} \in \mathbb{R}^3$ that weights stakeholder preferences, reducing spatial complexity by making interdependencies explicit. | 🗺️ Utility theory |
| **Implementation Benefits** | 🔐 What mathematical insights can guide optimal action sequencing? | $\nabla_{\textcolor{red}{A}} \textcolor{#3399FF}{U}(\textcolor{green}{S},\textcolor{red}{A})/C(\textcolor{red}{A})$ provides optimal action sequencing that maximizes utility per unit cost across stakeholder dimensions, enabling entrepreneurs to traverse the decision polyhedron efficiently. | 📐 Gradient-based optimization |
| **Implementation Approach** | 🔐 How can this mathematical framework be implemented in practice? | Through industry-parameterized xarray datasets with explicit dimensions and variables, enabling visualization of decision paths across AI, climate, and robotics mobility ventures. | 💸 Data-driven decision support systems |
### Simple Words Version
| Section | Question | Answer | Literature Brick |
|---------|----------|--------|------------------|
| **Problem** | 🔐 Why do entrepreneurs struggle with decision-making? | Existing entrepreneurial decision models are too complicated to use in real life. They involve too many moving parts that affect each other, leading entrepreneurs to copy others' behaviors instead of figuring out what works best for their unique situation. | 🧍♀️ Cognitive limitations in decision-making |
| **Cause (nature)** | 🔐 What makes entrepreneurial decisions naturally difficult? | Decisions in one area affect $\textcolor{#3399FF}{outcomes}$ in others (spatial complexity) and today's choices shape tomorrow's opportunities (temporal complexity). This creates a tangled web that's impossible to solve without a structured approach. | 🌏 Complex adaptive systems |
| **Root Cause 2 (individual)** | 🔐 What specific challenges do individual entrepreneurs face when making decisions? | Entrepreneurs don't clearly know what they $\textcolor{purple}{value}$ most (customer satisfaction? investor returns? operational excellence?), nor do they understand how their $\textcolor{red}{actions}$ connect to $\textcolor{#3399FF}{outcomes}$ or what each $\textcolor{red}{action}$ costs them in resources. | 🧍♀️ Value clarification theory |
| **Solution Framework** | 🔐 What approach can help entrepreneurs make better decisions? | A step-by-step decision-making approach that helps entrepreneurs balance what different stakeholders need while staying within their available resources. | 📐 Structured decision analysis |
| **KF1: Informing Function** | 🔐 How can entrepreneurs better understand the consequences of their actions? | Shows entrepreneurs how their $\textcolor{red}{actions}$ will likely change their $\textcolor{green}{situation}$ based on their specific industry (AI, climate, or robotics). This helps them see the connection between what they do today and what opportunities they'll have tomorrow. | 🧭 Scenario planning |
| **KF2: Calibration Function** | 🔐 How can entrepreneurs align their actions with what they truly value? | Helps entrepreneurs figure out exactly how much they $\textcolor{purple}{value}$ different stakeholders (customers, partners, investors) and how different changes in their business affect each stakeholder's $\textcolor{#3399FF}{satisfaction}$. | 🗺️ Stakeholder theory |
| **Implementation Benefits** | 🔐 What practical benefits does this approach offer entrepreneurs? | Gives entrepreneurs a clear map of which $\textcolor{red}{actions}$ give the most "$\textcolor{#3399FF}{benefit}$ for their buck" at each step, allowing them to make smarter decisions that align with their $\textcolor{purple}{priorities}$. | 💸 Resource allocation optimization |
| **Implementation Approach** | 🔐 How can entrepreneurs actually use this framework in their business? | An interactive tool that visualizes decision paths, compares outcomes across industries, and helps entrepreneurs see how their unique $\textcolor{purple}{values}$ lead to different optimal strategies. | 📐 Decision support systems |