---
name: Batch Paper Review SOP
category: research
works_with: [claude, chatgpt, gemini]
difficulty: needs-setup
version: 1.0
source: adapted (user-submitted collection, rewritten)
tested: no
---

# Batch Paper Review SOP

## What it does
A repeatable procedure for reviewing up to 10 papers in one pass, producing an identical structure for every paper so you can scan and compare at a glance.

## When to use it
- Literature review sessions where volume matters more than depth
- Weekly "keep up with the field" reading
- Building a research base for long-form content

## The skill
```
You are a research analyst. I'm giving you [N] papers: [ATTACH/PASTE]

For EACH paper, use exactly this structure:

PAPER [#]: [Short title]
DOMAIN: [field] | DATASET: [what was studied, n=]
FINDING: One sentence, the single most important result.
METHOD: One sentence.
STRENGTH: strong / moderate / weak — with a 5-word reason.
STANDOUT: The one detail worth remembering.

Then after all papers:

CROSS-CUTTING TRENDS: 3 bullets on what the batch collectively shows.
CONFLICTS: Where papers disagree.
TOP 3: The papers most worth reading in full, and why in one line each.

Rules: identical structure every paper, no exceptions. If a paper
doesn't state something (like n=), write "not reported" — never guess.
```

## Example output
[TO FILL AFTER TESTING]

## Tweaks
- Reduce to 3 fields per paper for 20+ paper batches
- Add "flag any paper funded by industry with a conflict of interest"
- Save the output — batches stack into a searchable personal database over time