Catalog and summarize papers dropped into Drive
An n8n workflow extracts metadata from new PDFs, finds related papers on Semantic Scholar and PubMed, builds an APA citation, logs to Sheets and creates a Notion summary. Task: Suggested implementation: Configure an n8n workflow triggered by new PDFs in a Google Drive folder. Use the PDF Vector node to extract metadata, abstract, study type, and findings. Search Semantic Scholar and PubMed using top keywords, generate APA citations, and log results to Google Sheets and Notion. Human role: Review extracted data for accuracy before finalizing records.; tools: n8n. Human role: The original post does not say how a person stayed involved.; limitations: Requires self-hosted n8n. PDF Vector consumes credits (approx. 4-5 per paper), limiting free tier usage to ~20-25 papers/month. Source reliability is low due to 404 error. Human approval is necessary for niche topics or scanned documents where accuracy may drop..
Tools
Published on Agent Work Atlas:
Overview
An n8n workflow extracts metadata from new PDFs, finds related papers on Semantic Scholar and PubMed, builds an APA citation, logs to Sheets and creates a Notion summary.
Workflow
Suggested implementation: Configure an n8n workflow triggered by new PDFs in a Google Drive folder. Use the PDF Vector node to extract metadata, abstract, study type, and findings. Search Semantic Scholar and PubMed using top keywords, generate APA citations, and log results to Google Sheets and Notion. Human role: Review extracted data for accuracy before finalizing records.
Reported result
Outcome unknown as source is unavailable. Proposed acceptance check: Verify that 95% of digital PDFs yield correct metadata and that related paper searches return relevant results within 30 seconds per document.
Human role
The original post does not say how a person stayed involved.
Limitations
Requires self-hosted n8n. PDF Vector consumes credits (approx. 4-5 per paper), limiting free tier usage to ~20-25 papers/month. Source reliability is low due to 404 error. Human approval is necessary for niche topics or scanned documents where accuracy may drop.
Try it
Act as an automation engineer. I need to build a literature review assistant in n8n. [replaceable inputs: Google Drive folder ID, Notion database ID, Google Sheets ID]. Steps: 1. Create a Google Drive trigger for new PDFs. 2. Add PDF Vector node to extract metadata, abstract, study type, and findings. 3. Use top 3 keywords to search Semantic Scholar and PubMed. 4. Format results into APA citations. 5. Append rows to Google Sheets and create Notion pages. 6. Dry run with 5 sample PDFs (3 digital, 2 scanned). 7. Measure processing time and metadata accuracy. 8. Require my confirmation before scaling to full folder. Handle errors by logging failed extractions to a separate sheet. Do not publish or spend credits without my explicit approval.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.