Extract Data from Papers → Analyze Patterns → Generate Research Insights
Transform scattered research findings into actionable insights by extracting key data points from multiple papers and identifying trends across studies.
Workflow Steps
ChatGPT
Extract structured data from papers
Upload research papers or paste abstracts into ChatGPT. Request extraction of key data points: sample sizes, methodologies, results, effect sizes, and confidence intervals. Ask for output in CSV format with consistent column headers.
Airtable
Create research database
Import the CSV data into Airtable. Set up views to filter by methodology, publication year, sample size, and effect size. Create linked record fields to connect related studies and add rating fields for study quality assessment.
Airtable
Analyze patterns and trends
Use Airtable's summary fields and grouping features to identify trends across studies. Calculate average effect sizes, success rates by methodology, and temporal patterns. Create charts showing research evolution over time.
Claude
Generate research synthesis report
Export the organized data and patterns from Airtable. Ask Claude to create a comprehensive synthesis report identifying key findings, research gaps, conflicting results, and recommendations for future studies.
Workflow Flow
Step 1
ChatGPT
Extract structured data from papers
Step 2
Airtable
Create research database
Step 3
Airtable
Analyze patterns and trends
Step 4
Claude
Generate research synthesis report
Why This Works
ChatGPT excels at extracting structured data from unstructured text, Airtable provides powerful organization and analysis tools, while Claude synthesizes complex findings into clear insights.
Best For
Researchers conducting meta-analyses or systematic reviews across multiple studies
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