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significantly predicted » significantly reduced (Expand Search), significantly reduce (Expand Search), significant predictor (Expand Search)
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Showing 81 - 100 results of 59,738 for search '(( significant ((main decrease) OR (mean decrease)) ) OR ( significantly predicted based ))', query time: 0.80s Refine Results
  1. 81
    Negative binomial relationship between sea surface temperature (SST) and daily mean point-count abundance for the six most abundant taxa with statistically significant (p<0.05) relationships across the 12 intertidal sites within the Main Hawaiian Islands from 2004–2019.

    Negative binomial relationship between sea surface temperature (SST) and daily mean point-count abundance for the six most abundant taxa with statistically significant (p<0.05) rel... by Rebecca J. Ward (9872202)

    Published 2023
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  2. 82
    The map of the study site in Jiangling County, Hubei Province, People’s Republic of China.

    The map of the study site in Jiangling County, Hubei Province, People’s Republic of China. by Jiaxin Feng (4926844)

    Published 2023
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  3. 83
    Changes in the prevalence of schistosomiasis infection in humans, livestock, and snails in Jiangling County from 2005 to 2021.

    Changes in the prevalence of schistosomiasis infection in humans, livestock, and snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  4. 84
    Global Moran’s <i>I</i> spatial autocorrelation analysis on average density of living snails in Jiangling County from 2005 to 2021.

    Global Moran’s <i>I</i> spatial autocorrelation analysis on average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  5. 85
    Local spatial autocorrelation analysis of the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/ngcc/ with credit to National Geomatics Center of China.

    Local spatial autocorrelation analysis of the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.... by Jiaxin Feng (4926844)

    Published 2023
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  6. 86
    Results of Joinpoint model analysis on trends of schistosomiasis-related epidemic indicators in Jiangling County from 2005 to 2021.

    Results of Joinpoint model analysis on trends of schistosomiasis-related epidemic indicators in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  7. 87
    Fig 4 -

    Fig 4 - by Jiaxin Feng (4926844)

    Published 2023
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  8. 88
    Central and discrete trend changes for the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/ngcc/ with credit to National Geomatics Center of China.

    Central and discrete trend changes for the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/... by Jiaxin Feng (4926844)

    Published 2023
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  9. 89
    Distribution of hot spot areas for the average density of living snails in Jiangling County from 2005 to 2021.

    Distribution of hot spot areas for the average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  10. 90
    Investigation results of schistosomiasis in humans, livestock and investigation on snails in Jiangling County from 2005 to 2021.

    Investigation results of schistosomiasis in humans, livestock and investigation on snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  11. 91
    Analysis of kernal density for the average density of living snails in Jiangling County from 2005 to 2021.

    Analysis of kernal density for the average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  12. 92
    Changes in the average density of living snails and the occurrence rate of frames with snails in Jiangling County from 2005 to 2021.

    Changes in the average density of living snails and the occurrence rate of frames with snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  13. 93
    FFD – main effect, original fibrosis burden.

    FFD – main effect, original fibrosis burden. by Åshild Telle (22794721)

    Published 2025
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  14. 94
    Mean density (g/m<sup>2</sup>) and whole survey area fish abundance (kg) estimated using mean <i>Sa</i> and set net catch ratio.

    Mean density (g/m<sup>2</sup>) and whole survey area fish abundance (kg) estimated using mean <i>Sa</i> and set net catch ratio. by Yanhui Zhu (6697751)

    Published 2021
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  15. 95
    Predicted cost of significant obstetric complication from fitted model.

    Predicted cost of significant obstetric complication from fitted model. by A. Thi Win Shwe (6490502)

    Published 2019
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  16. 96
    CONSORT diagram showing the flow of participants through each stage of the DOREPAR randomized trial for the main outcome (change of VAS).

    CONSORT diagram showing the flow of participants through each stage of the DOREPAR randomized trial for the main outcome (change of VAS). by Karel Joineau (21799908)

    Published 2025
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  17. 97
    Mean amplitude values during a complete 360° rotation for the iliocostalis muscle.

    Mean amplitude values during a complete 360° rotation for the iliocostalis muscle. by Christoph Anders (4068499)

    Published 2024
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  18. 98
    Mean amplitude values during a complete 360° rotation for the longissimus muscle.

    Mean amplitude values during a complete 360° rotation for the longissimus muscle. by Christoph Anders (4068499)

    Published 2024
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  19. 99
    Mean amplitude values during a complete 360° rotation for the multifidus muscle.

    Mean amplitude values during a complete 360° rotation for the multifidus muscle. by Christoph Anders (4068499)

    Published 2024
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  20. 100
    Number of CTD inferred g2p edges discovered with cluster predicted to be significant vs non-significant based on the four thresholds.

    Number of CTD inferred g2p edges discovered with cluster predicted to be significant vs non-significant based on the four thresholds. by Michael S. Bradshaw (11772750)

    Published 2024
    “…<p>Number of CTD inferred g2p edges discovered with cluster predicted to be significant vs non-significant based on the four thresholds.…”
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