Showing 1,401 - 1,420 results of 17,884 for search 'significant ((((gap decrease) OR (((nn decrease) OR (teer decrease))))) OR (a decrease))', query time: 0.66s Refine Results
  1. 1401
  2. 1402

    S1 File - by Michael Gulledge (20577135)

    Published 2025
    “…Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions. …”
  3. 1403

    Absolute β convergence results. by Ke Liu (121889)

    Published 2025
    “…Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. …”
  4. 1404

    Conditional β convergence results. by Ke Liu (121889)

    Published 2025
    “…Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. …”
  5. 1405

    Markov transition probability matrix (k = 4). by Ke Liu (121889)

    Published 2025
    “…Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. …”
  6. 1406

    Markov transition probability matrix (k = 4). by Ke Liu (121889)

    Published 2025
    “…Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. …”
  7. 1407

    Regression results. by Ke Liu (121889)

    Published 2025
    “…Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. …”
  8. 1408
  9. 1409

    SHAP dependence plots with interaction coloring. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  10. 1410

    Screening process diagram. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  11. 1411

    SHAP waterfall plot. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  12. 1412

    SHAP decision plot. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  13. 1413

    LASSO regression visualization plot. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  14. 1414

    SHAP dependence plots. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  15. 1415

    Tertile stratified subgroup analysis. by Wentao Yang (205781)

    Published 2025
    “…This study examines the eGDR-frailty link, develops a machine learning predictive model to address this gap, and explores diabetes mellitus (DM) as a mediator, providing new insights for clinical intervention.…”
  16. 1416

    Table 1_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

    Published 2025
    “…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
  17. 1417

    Table 3_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

    Published 2025
    “…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
  18. 1418

    Table 4_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

    Published 2025
    “…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
  19. 1419

    Table 8_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

    Published 2025
    “…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
  20. 1420

    Table 2_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.xlsx by Stefanie Wagner (743707)

    Published 2025
    “…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”