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linear decrease » linear increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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3781
Models 1 to 6: estimation results.
Published 2025“…<div><p>Despite the significance of economic freedom in tourism dynamics, especially from a spatial standpoint, its nuanced influence remains unexplored mainly in current research. …”
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3782
Hausman test results.
Published 2025“…<div><p>Despite the significance of economic freedom in tourism dynamics, especially from a spatial standpoint, its nuanced influence remains unexplored mainly in current research. …”
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3783
Variable’s construction.
Published 2025“…<div><p>Despite the significance of economic freedom in tourism dynamics, especially from a spatial standpoint, its nuanced influence remains unexplored mainly in current research. …”
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3784
Moran’s I across countries.
Published 2025“…<div><p>Despite the significance of economic freedom in tourism dynamics, especially from a spatial standpoint, its nuanced influence remains unexplored mainly in current research. …”
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3785
Raw dataset.
Published 2025“…<div><p>Despite the significance of economic freedom in tourism dynamics, especially from a spatial standpoint, its nuanced influence remains unexplored mainly in current research. …”
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3786
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3787
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3788
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3789
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3790
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3791
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3792
Enhanced Reaction Kinetics in Stationary Two-Phase Flow through Porous Media
Published 2025“…The global kinetics initially increase before experiencing a monotonic decrease with significant fluctuations caused by the displacement of the nonwetting phase. …”
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3793
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3794
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3795
Assessment values of machine learning models.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
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3796
List of datasets in AqSolDB.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
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3797
Feature importance derived from SHAP analysis.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
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3798
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3799
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3800
Learn!Bio study: Grouping of Participants.
Published 2025“…The Covid-19 pandemic and the consequent restriction of personal social interaction resulted in an significant decrease in the mental wellbeing of undergraduate bioscience students in this study, cumulating in poor or very poor self-rating of wellbeing in spring 2021; while at the same time students showed evidence of advanced adaption to the new learning and social environment by acquisition of additional technical, social and professional graduate-level skills. …”