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原文摘要

As artificial intelligence (AI) becomes more common in scientific writing, some authors show fewer signs of AI assistance than expected across successive periods. We analysed OpenAlex publication histories for 71,133 authors with at least one eligible first-authored English-language publication each year from 2023 through September 2026. Using abstract-based writing scores, we defined resistance as the predicted minus observed share of abstracts classified as AI-assisted. Positive scores indicate fewer such abstracts than expected. Early resistance was positively associated with later resistance, although the share with positive scores fell. Environmental characteristics contributed more than individual characteristics to predicting later scores, although overall predictive power was low. Having a collaborator with a non-positive early score was associated with lower subsequent resistance. Authors with positive mean scores in both 2023-2024 and 2025-2026 cited older work, drew on fewer subfields and more often cited sources they had used before than authors with non-positive mean scores in both periods. These differences were evident before 2023. The adjusted gap in reference reuse rose from 3.24 percentage points before 2023 to 7.95 in 2025-2026. The findings link variation in signs of AI assistance to earlier differences in how scientists used prior work.