132,455 research outputs found

    Bray-Curtis similarity matrix

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    Contains the Bray-Curtis similarity between each pair of evolved populations. This file is produced by the Bray-Curtis calculations R script

    Bray-Curtis dissimilarity distances, colored by measures of physical activity.

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    (A) Bray-Curtis dissimilarity distances, colored by physically active status. PERMANOVA R2 = 0.004 (P = 0.001). SHOW, 2016–2017. (B) Bray-Curtis dissimilarity distances, colored by quartile of MVPA minutes per week. PERMANOVA R2 = 0.003 (P = 0.001). SHOW, 2016–2017. (C) Bray-Curtis dissimilarity distances colored by engagement in any active transportation. R2 = 0.003 (P = 0.009). SHOW, 2016–2017. (D) Bray-Curtis dissimilarity distances, colored by quartile of minutes in active transportation per week, excluding participants who reported no active transportation (n = 147). PERMANOVA R2 = 0.004 (P = 0.92). SHOW, 2016–2017.</p

    Bray-Curtis calculations R script

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    This script uses Breseq_Output_with_verification.txt data file. It tests whether there is a significant difference in mutation number between treatments, calculates the Bray-Curtis pairwise similarity between each pair of populations, and conducts randomization tests

    Harold B. Bray

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    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    General Correspondence, Mission; 1898-1899; Young, Seymour B.

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    Letters between John Mills Whitaker and Seymour B. Young and Isaac Bray Young, 1898Letter dated 14 January 1898 at Salt Lake City, Utah, from Seymour B. Young to John M. Whitaker; Letter dated 20 January 1898 at Salt Lake City, Utah, from Seymour B. Young to John M. Whitaker; Note (undated) from Seymour B. Young to John M. Whitaker; Letter from Isaac Bray Young to John M. Whitake

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Bray, Ann B.

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    Body cremated. Ernest Coke Bray - husbandhttps://stars.library.ucf.edu/cfm-ch-memoranda-1939/1112/thumbnail.jp
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