Showing 301 - 320 results of 18,014 for search 'significant ((((gap decrease) OR (((we decrease) OR (teer decrease))))) OR (a decrease))', query time: 0.49s Refine Results
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    Table 2 - by Rosanna Mary Rooney (17595801)

    Published 2024
    “…Despite a global decrease over the last 30 years, youth crime remains prevalent. …”
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    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. …”
  4. 304

    Marginal means – Pooled across scenarios. 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. …”
  5. 305

    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. …”
  6. 306

    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. …”
  7. 307

    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. …”
  8. 308

    AMCEs – Pooled across scenarios. 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. …”
  9. 309

    Methodological flowchart. 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. …”
  10. 310

    Preference for the EIA vs. ETA across scenarios. 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. …”
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    Contrasting Size Dependence of Photochemical Lifetimes of Polypropylene and Expanded Polystyrene Microplastics in Surface Waters by Ariana Patterson (22764051)

    Published 2025
    “…Sunlight-driven photochemistry can dissolve buoyant microplastics, producing dissolved organic carbon (DOC). We hypothesized that plastic dissolution would increase linearly with increasing surface area (SA)-to-volume (V) ratio as plastics decrease in size. …”
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    Participant retention flowchart. by Carolin Oetzmann (11397968)

    Published 2025
    “…We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. …”
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    Cohort characteristics. by Fernanda Talarico (807333)

    Published 2024
    “…</p><p>Results</p><p>The analysis reveals a significant decrease in all health services utilization from 2016 to 2019, followed by an increase until 2022. …”
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    Magnification X2 of Fig 4A. by Huan W. Yang (19746645)

    Published 2024
    “…<i>intracellularis</i> infection. In this study, we investigated the nuclear factor-<b>κ</b>B (NF-κB)-regulated immune response against infection of a clinical strain Dkp23 and a live-attenuated Enterisol vaccine strain in PK-15 cells. …”