Showing 141 - 160 results of 140,032 for search '(( significant models based ) OR ( significant ((a decrease) OR (nn decrease)) ))', query time: 2.24s Refine Results
  1. 141

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD4 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD4 dataset.…”
  2. 142

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD7 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD7 dataset.…”
  3. 143

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD3 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD3 dataset.…”
  4. 144

    MAE significance comparison between MSCALSTM and baseline models based on PeMSD8 dataset. by Zhifei Yang (14613332)

    Published 2025
    “…<p>MAE significance comparison between MSCALSTM and baseline models based on PeMSD8 dataset.…”
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    Dynorphin Neuropeptides Decrease Apparent Proton Affinity of ASIC1a by Occluding the Acidic Pocket by Lilia Leisle (11356934)

    Published 2021
    “…Prolonged acidosis, as it occurs during ischemic stroke, induces neuronal death via acid-sensing ion channel 1a (ASIC1a). Concomitantly, it desensitizes ASIC1a, highlighting the pathophysiological significance of modulators of ASIC1a acid sensitivity. …”
  15. 155

    Dynorphin Neuropeptides Decrease Apparent Proton Affinity of ASIC1a by Occluding the Acidic Pocket by Lilia Leisle (11356934)

    Published 2021
    “…Prolonged acidosis, as it occurs during ischemic stroke, induces neuronal death via acid-sensing ion channel 1a (ASIC1a). Concomitantly, it desensitizes ASIC1a, highlighting the pathophysiological significance of modulators of ASIC1a acid sensitivity. …”
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    Reduced (owner-animal metadata) XGBoost model on the <i>significant illness</i> binary using the primary decision-maker dataset. by Richard Barrett-Jolley (739341)

    Published 2024
    “…Acceptance threshold is indicated by the colour bar on the right-hand side, and also shown at discrete points on the curve. For example, with a threshold probability of 0.05, the model correctly predicts approximately 73% of dogs where the <i>significant illness</i> outcome was classified as ‘yes’, but the false-positive rate is approximately 45%. …”
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