^ This. Also, in my experience, if you're on a student budget, Afforai AI Research Assistant Reference-based Summarization is a lifesaver. I've tried many tools, and this one actually links every claim to a page number so it dont hallucinate your genomic data. Practical stuff to try:

• Use the 'reliable' mode for methodology extraction
• Cross-check the linked citations immediately It stays way more coherent than Claude for long sequences, and it's cheaper too.

I would suggest looking into Elicit Plus Academic Research Assistant for your thesis work. It uses a methodical extraction process instead of just generating a summary. You might want to consider:

• SciSpace Premium Research Platform for the specific literature review workspace.
• Perplexity AI Pro Research Model for cross-referencing citations. Be careful with long PDFs though, as many tools use RAG which can still miss data in the middle of the document.

bump

^ This. Just catching up and I agree, tho I'd suggest being careful.

• Humata AI Enterprise Document Analysis is best for verification.
• Scholarcy Library Personal Research Librarian is safer for summaries.

In my experience, dealing with those massive genomic papers is a total nightmare for standard models. Over the years, I've tried many different tools because I'm always worried about hallucinations in my own research. Honestly, for something as dense as 80-page sequences, you should look at Google NotebookLM Gemini 1.5 Pro. It uses a grounded approach where it only pulls from your uploaded files, which makes it way more reliable than standard chatbots. It handles the context window issue much better than OpenAI GPT-4o Multimodal Model does. I've also tried Anthropic Claude 3.5 Sonnet 200k Context Window, which is decent, but it sometimes glosses over the methodology unless you're super specific. If you want to stay safe for your thesis, NotebookLM is the way to go since it lets you click citations to verify the text. It's much more methodical... just feels safer for academic work.