Fig. 4: Prize characteristics predict the magnitude of extraordinary growth.

a through c show the raw data relationship between a prize’s characteristics and the estimated magnitude of \({\Delta }_{10}\) on 6 growth measures (***p < 0.001; **p < 0.01; and *p < 0.05). The color dots with error bars represent the mean value and 95% CI, the center line of the black box plot is the median, box limits correspond to the data’s first and third quartiles, and violin shades represent the data’s distribution. Two-sided t-test are used in these analyses. The p-value for a ranges from \(2.70\times {10}^{-180}\) to \(5.30\times {10}^{-67}\), for c ranges from \(1.60\times {10}^{-25}\) to \(9.06\times {10}^{-9}\), and for b p-value ranges from 0.0017 to 0.013 except for lead scientist impact (p-value = 0.374). Sample sizes for topics associated with prizes with recency, money, and discipline specific are n = 5672 (46.73%), n = 6102 (50.27%), and n = 8812 (72.59%) respectively. d–f show the standardized coefficient from a regression of \({\Delta }_{10}\) on all three prize characteristics, indicating the significant and substantive association between prize characteristics and the magnitude of the expected level of extraordinary growth in a topic after it is associated with a prize. Control variables are lagged \({\Delta }_{t}\) at t = −1, −2, −3, discipline, year, prize visibility and reputation, and prizewinner status. Error bars demonstrate 95% CI. Please see Supplementary Tables S2–S10 for details of regression analyses and further robustness checks.