Search alternatives:
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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7481
Preference for the EIA – conjoint results.
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. …”
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7482
Sample attribute table.
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. …”
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7483
Subgroup analysis – Political affiliation.
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. …”
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7484
Sample scenario description.
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. …”
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7485
AMCEs – Pooled across scenarios.
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. …”
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7486
Methodological flowchart.
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. …”
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7487
Preference for the EIA vs. ETA across scenarios.
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. …”
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7488
Data Sheet 1_Metabolic adaptation fluctuates with different prediction equations: a secondary analysis based on a weight-loss clinical trial.docx
Published 2025“…Both Katch-McArdle-determined RMR and BIA-determined RMR presented a significant decrease between baseline and the end of the intervention (week 16). …”
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7489
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7490
Identification of narciclasine as a novel NRF2 inhibitor
Published 2025“…Finally, we observed that administration of narciclasine significantly decreased the growth of A549 xenografts. …”
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7491
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7492
Mediating effect of sexual interest in a sibling.
Published 2024“…Instead, constant proximity was related to a decreased chance that sibling incest had occurred, through its relationship with sexual interest in a sibling.…”
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7493
VB2 cell fate analysis of <i>hlh-17</i>, <i>hlh-31</i>, and <i>hlh-32</i> mutant animals.
Published 2025“…Error bars indicate standard deviation of the mean. ****<i>p</i> ≤ 0.0001, *<i>p</i> ≤ 0.05, ns: not significant. …”
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7494
Telomere length (TL) in maternal blood samples.
Published 2025“…<p>A. Age-dependent decrease in the leukocyte TL in the control groups of the study, comparing pregnant and non-pregnant women. …”
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7495
Typical structure of a centrifugal nozzle [25].
Published 2025“…As temperature rises from 0°C to 50°C, liquid film thickness decreases, with a reduction of 14.6% for low-blending fuel and 52.8% for high-blending fuel.…”
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7496
Patients’ responses to EQ5-D items.
Published 2024“…Moreover, patients with only an elementary education had significantly lower EQ5-D scores compared to those with a postgraduate education (-0.106, 95%CI (-0.190, -0.023), p = 0.013).…”
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7497
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7498
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7499
Multiple comparisons after ANOVA(CR10).
Published 2025“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”
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7500
Homogeneity test of CR10.
Published 2025“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”