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Showing 1 - 20 results of 30 for search '(( significantly ((greater decrease) OR (a decrease)) ) OR ( significant predictors decrease ))~', query time: 0.40s Refine Results
  1. 1
    Model-averaged coefficients, significance, and relative importance (RI) of the predictor variables for the GLMMs to evaluate effects on: (A) overall pollinator abundance; (B) fruit production per female tree, (C) seed production per female tree; and (D) seed weight. Farming system refers to ecological vs. conventional practices; CCA1 refers to the first axis of the CCA and depicts the relationship between the % of natural habitats in the landscape and the composition of the pollinator community (increase abundance of wild bees with the increase in natural habitats); Male-to-female ratio and Male-to-female ratio<sup>2</sup> indicate linear and quadratic terms, respectively. Significant <i>p</i>-values are marked in bold. RI was estimated by summing the Akaike weights over all the models where each explanatory variable appeared, and highlights the importance of these variables in the models [75].

    Model-averaged coefficients, significance, and relative importance (RI) of the predictor variables for the GLMMs to evaluate effects on: (A) overall pollinator abundance; (B) fruit... by Carmelo Gómez-Martínez (9384385)

    Published 2025
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  2. 2
    BMI versus change in soft tissue thickness in hydrated to dehydrated state.

    BMI versus change in soft tissue thickness in hydrated to dehydrated state. by Fatemeh Khorami (22041563)

    Published 2025
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  3. 3
    Data.

    Data. by Su Hwan Park (15158181)

    Published 2025
    “…In the univariate analysis, ERM area reduction at 6 months was a significant predictor of vision loss (odds ratio, 1.632; P = 0.002). …”
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  4. 4
    Changes in best-corrected visual acuity and total area reduction ratio of the epiretinal membrane (ERM) during follow-up.

    Changes in best-corrected visual acuity and total area reduction ratio of the epiretinal membrane (ERM) during follow-up. by Su Hwan Park (15158181)

    Published 2025
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  5. 5
    Baseline characteristics of patients.

    Baseline characteristics of patients. by Su Hwan Park (15158181)

    Published 2025
    “…In the univariate analysis, ERM area reduction at 6 months was a significant predictor of vision loss (odds ratio, 1.632; P = 0.002). …”
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  6. 6
    Boxplots of food-security metrics by household asset categories.

    Boxplots of food-security metrics by household asset categories. by Daniel Fobi (13607663)

    Published 2024
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  7. 7
    Graphical output of results from movement counts data modeled as a function of treatment levels, week, and time discretized into 3-hour categories.

    Graphical output of results from movement counts data modeled as a function of treatment levels, week, and time discretized into 3-hour categories. by Kevin O. Ochwedo (11032248)

    Published 2025
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  8. 8
    Graphical output of results from movement counts data modeled as a function of treatment levels, temperature ranges, and time discretized into 3-hour categories.

    Graphical output of results from movement counts data modeled as a function of treatment levels, temperature ranges, and time discretized into 3-hour categories. by Kevin O. Ochwedo (11032248)

    Published 2025
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  9. 9
    Matched data.

    Matched data. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  10. 10
    Nomogram model.

    Nomogram model. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  11. 11
    Flowchart of Study Design and Analysis.

    Flowchart of Study Design and Analysis. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  12. 12
    Multivariate Binary Logistic Regression Analysis.

    Multivariate Binary Logistic Regression Analysis. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  13. 13
    ROC curve.

    ROC curve. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  14. 14
    Unmatched data.

    Unmatched data. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  15. 15
    Calibration curve.

    Calibration curve. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  16. 16
    Decision curves.

    Decision curves. by Feng Zhang (6548)

    Published 2025
    “…The observation group showed significantly lower levels of white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYM), red blood cell count (RBC), hemoglobin (HGB), and albumin (ALB) compared to the control group (P < 0.05). …”
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  17. 17
    Relationship of different levels of physical activity on the health status of long-term breast cancer survivors: a cross-sectional study

    Relationship of different levels of physical activity on the health status of long-term breast cancer survivors: a cross-sectional study by Francisco Álvarez-Salvago (21338477)

    Published 2025
    “…This inactivity is significantly correlated with greater physical and emotional deterioration.…”
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  18. 18
    Data Sheet 1_Perceived protective behavioral changes in Chinese residents post-dynamic zero-COVID policy lifting: a cross-sectional study.docx

    Data Sheet 1_Perceived protective behavioral changes in Chinese residents post-dynamic zero-COVID policy lifting: a cross-sectional study.docx by Yuan-Yuan Song (6287387)

    Published 2024
    “…The mean scores for the two vaccination-related items were significantly greater than the hypothesized no-change value of 2 (p < 0.001). …”
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  19. 19
    Table 1_Pre-COVID era pediatric disease incidence in Kazakhstan: regional panel data analysis of multiple disease groups (2010–2019).xlsx

    Table 1_Pre-COVID era pediatric disease incidence in Kazakhstan: regional panel data analysis of multiple disease groups (2010–2019).xlsx by Nurlan Smagulov (21510632)

    Published 2025
    “…A 1% increase in population density correlated with a 1.05% decrease in respiratory disease incidence (p = 0.008), whereas unemployment was linked to a 0.41% rise (p = 0.029). …”
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  20. 20
    Climate is more influential to vegetation green-up than factors that contribute to erosion following high-severity wildfire

    Climate is more influential to vegetation green-up than factors that contribute to erosion following high-severity wildfire by Joseph Crockett (22077659)

    Published 2025
    “…While the effects of year-of-fire factors related to erosion were significant, they were small, and the variability explained by growing season vapor pressure deficit and growing season precipitation were significantly greater.…”
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