Academic Engines
Every CitationLab post tagged academic engines. This topic runs through several posts across the blog — case files where it caused a real problem, and guides for handling it in your own reference list.
Can AI invent fake references? Ours can't — by construction
The operation that produces fabricated references — generate a plausible source — is not implemented. What the model is actually asked, where references come from instead, and the one guard we removed on purpose.
Deterministic first, AI second — and why the order is the whole design
Why CitationLab settles what it can with rules before any model is consulted, and what that ordering buys you in a reference check you can actually verify.
How we find the newer version: seven engines, one verdict
Crossref, PubMed, Semantic Scholar, OpenAlex and the scraped tiers, asked in a fixed order. Why free-first is a metadata-quality rule, and what the engine ledger reveals.
It missed 27 citations, then told me it had found the last one
A general-purpose assistant missed 27 citations in one thesis chapter and said each time that it had found the last. That failure is why CitationLab runs rules before models.
We check the references you already had, not just the ones we found
A citation check that only reports what is missing leaves the risky part untouched. Every reference in your bibliography is independently resolved — including the DOI you supplied, which is followed to see what it actually describes.