plot-logic-pipeline

# Plot-Logic-Pipeline Systematically deconstruct scientific papers by following the figure-discussion logical backbone. ## When to Use - Analyzing a research paper's argument structure - Reviewing manuscripts before submission - Understanding how figures support claims in technical papers - Mapping evidence sources (literature vs. new measurements) - Identifying logical gaps or unsupported claims ## Core Principle **Figures are the bare bones of a paper's logic flow.** Each figure corresponds to a discussion that either: - **Sets up** the next key finding (preparation) - **States** the key finding (conclusion) Complete understanding requires analyzing every figure-discussion pair and tracking evidence sources. ## Analysis Framework ### Step 1: Figure Inventory Create a complete inventory of all figures in the paper: ``` Figure 1: [Brief description] Figure 2: [Brief description] ... Figure N: [Brief description] ``` ### Step 2: Figure-Discussion Mapping For each figure, identify its corresponding discussion section and analyze: ``` Figure X: [Description] ├── Location: [Section/page where discussed] ├── Discussion Type: [Setup / Statement] ├── Main Claim: [Key finding or point] └── Evidence Source: ├── Previous Study: [Citation(s) if supported by literature] ├── This Paper: [Analysis method if new measurement/calculation] └── Support Level: [Strong / Partial / Contradictory / Missing] ``` ### Step 3: Logic Flow Reconstruction Map how figures build upon each other: ``` Paper Logic Flow: Figure 1 → Figure 2 → Figure 3 → ... → Conclusion ↓ ↓ ↓ [Setup] [Key Finding 1] [Key Finding 2] ``` ### Step 4: Evidence Assessment Evaluate the strength of the paper's argument: - Are all major claims supported by figures? - Are evidence sources properly attributed? - Are there logical gaps between figures? - Do setup discussions adequately prepare for key findings? ## Evidence Classification ### Previous Study Support - **Direct citation**: Specific reference supporting the claim - **Literature consensus**: Multiple citations building consensus - **Comparative reference**: Contrasting with previous work ### This Paper's Contributions - **New experimental data**: Novel measurements with method specified - **Novel calculations**: Computational work or modeling - **Reanalysis**: New interpretation of existing data ### Combined Evidence - **Validation**: New data confirms previous studies - **Extension**: New data builds upon previous work - **Contradiction**: New data challenges previous findings ## Analysis Templates See [TEMPLATES.md](references/TEMPLATES.md) for detailed templates including: - Basic figure-discussion analysis - Complete paper analysis workflow - Materials science specific templates - Quality assurance checklist ## Quality Checks Before concluding analysis: - ✅ All figures mapped to discussions - ✅ Evidence sources identified for major claims - ✅ Logic flow clearly traced from introduction to conclusion - ✅ Setup vs. statement discussions distinguished - ✅ Contradictions or gaps noted and flagged ## Common Pitfalls - **Skipping "obvious" figures**: Even simple schematics contribute to logic flow - **Missing evidence attribution**: Always identify if claims come from citations or new work - **Ignoring setup discussions**: These are crucial for understanding logical progression - **Overlooking figure details**: Axis labels, error bars, and annotations often contain key information - **Conflating correlation with causation**: Note when figures show correlation vs. when claims assert causation ## Rules 1. **Every figure gets analyzed** — no skipping, even if it seems straightforward 2. **Always classify evidence** — distinguish previous work from new contributions 3. **Trace the logic chain** — show how each figure builds on the previous one 4. **Flag gaps honestly** — note missing evidence or weak logical connections 5. **Separate observation from interpretation** — what the figure shows vs. what the authors claim