Uncensored AI for molecular biology literature review
Thirty papers into one table, with the disagreements still visible
A literature review is a table nobody wants to build: paper, question, method, finding, contradiction. The model does the first pass and flags where the field disagrees, which is the part you actually write.
Why the mainstream APIs fail here
A general model summarises each paper politely and flattens the contradictions, and a review with no contradictions in it is a list, not a review. The other option, pasting unpublished data alongside the papers into a service that trains on it, is the one your supervisor said not to do.
How Wild West API is used for this
Feed papers in batches and ask for the matrix row by row: question, model system, method, effect size, caveat. Ask where the findings conflict and what would resolve them.
A working loop
- Define the matrix columns before the first paper, not after the fifth.
- Ask for conflicts explicitly; they will not volunteer.
- Verify every citation exists before it goes in the draft.
Details are on the privacy page. Per-model prices are on /models and the pricing model is on /pricing.