Showing 581 - 600 results of 8,895 for search 'significant ((((gap decrease) OR (((teer decrease) OR (we decrease))))) OR (mean decrease))', query time: 0.50s Refine Results
  1. 581
  2. 582
  3. 583

    Volitional control frequency and intensity in VH (Kapsner-Smith et al., 2025) by Mara R. Kapsner-Smith (22139315)

    Published 2025
    “…Singers produced significantly smaller mean smallest changes of both <i>F</i>0 and intensity than nonsingers.…”
  4. 584
  5. 585
  6. 586
  7. 587
  8. 588
  9. 589
  10. 590
  11. 591
  12. 592
  13. 593
  14. 594
  15. 595
  16. 596

    Sound stress exposure prolonged the period of decreased withdrawal threshold after complete Freund’s adjuvant (CFA) injection. by Satoka Kasai (3861115)

    Published 2025
    “…(B) 50% withdrawal threshold in CFA-treated mice exposed to sound stress. They showed a significant decrease in 50% withdrawal threshold on day 7 after CFA injection, and CFA-treated mice exposed to sound stress showed a significant decrease in 50% withdrawal threshold during days 7–21 after CFA injection (CFA, on day 7, ****<i>P</i> < 0.001 vs day 0, on day 10, ***<i>P</i> < 0.001 vs day0; CFA + stress, day 7, 10, 14, and 21, ****<i>P</i> < 0.0001 vs day 0, Dunnett’s test). …”
  17. 597

    Preference for the EIA – conjoint results. by Mehdi Mourali (10170245)

    Published 2025
    “…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
  18. 598

    Sample attribute table. by Mehdi Mourali (10170245)

    Published 2025
    “…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
  19. 599

    Subgroup analysis – Political affiliation. by Mehdi Mourali (10170245)

    Published 2025
    “…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
  20. 600

    Sample scenario description. by Mehdi Mourali (10170245)

    Published 2025
    “…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”