Showing 1 - 20 results of 4,645 for search '(( across ((deep decrease) OR (mean decrease)) ) OR ( a ((large decrease) OR (marked decrease)) ))', query time: 0.46s Refine Results
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    Group-level narrow- and broad-band spectral changes after hemispherotomy reveal a marked EEG slowing of the isolated cortex, robust across patients. by Michele Angelo Colombo (22446342)

    Published 2025
    “…<p><b>(A)</b> The geometric mean of the PSD was taken first across electrodes, and subsequently across patients, for the observed PSD (main graph) as well as for the aperiodic fit of the PSD (corresponding to a straight line under logarithmic scale for both <i>x</i> and <i>y</i> axes, inset graph). …”
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    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. …”
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    <b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

    Published 2025
    “…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". …”
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    Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest. by Helal El-Zaatari (20442243)

    Published 2025
    “…<p>Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest.…”
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