186,843 research outputs found
Briley_OpenPracticesDisclosure_rev – Supplemental material for National Gross Domestic Product, Science Interest, and Science Achievement: A Direct Replication and Extension of the Tucker-Drob, Cheung, and Briley (2014) Study
No full textSupplemental material, Briley_OpenPracticesDisclosure_rev for National Gross Domestic Product, Science Interest, and Science Achievement: A Direct Replication and Extension of the Tucker-Drob, Cheung, and Briley (2014) Study by Anqing Zheng, Elliot M. Tucker-Drob and Daniel A. Briley in Psychological Science</p
Zheng_Supplemental_Material – Supplemental material for National Gross Domestic Product, Science Interest, and Science Achievement: A Direct Replication and Extension of the Tucker-Drob, Cheung, and Briley (2014) Study
No full textSupplemental material, Zheng_Supplemental_Material for National Gross Domestic Product, Science Interest, and Science Achievement: A Direct Replication and Extension of the Tucker-Drob, Cheung, and Briley (2014) Study by Anqing Zheng, Elliot M. Tucker-Drob and Daniel A. Briley in Psychological Science</p
Brileyetal2018_FigS2.tif
No full textFigure S2 associated with Briley PM, Liddle EB, Groom MJ, Smith HJF, Morris PG, Colclough GL, Brookes MJ, Liddle PF (2018). The development of human electrophysiological brain networks. Journal of Neurophysiology.The differences in beta band connectivity between adults and adolescents (A) and between adolescents and children (B). Connectivities are averaged across the pairs of ROIs within each of the four networks. See also Figure 3D, which shows the differences between adults and children. Asterisks show uncorrected p-values: * p</div
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Briley et al Sticky-flares Supplementary Movie 1
No full text<p>Originally published as Supplementary Movie 1 in Briley <em>et al</em>. (doi: 10.1073/pnas.151058111), this is a processed version of the original file provided by Chad Mirkin.</p>
<p>The punctate fluorescent signal is spatially correlated with the dark objects in the transmitted light channel, which are likely vesicles (on average about 0.8um in diameter). Single fluorescently-labelled mRNA would be visible as a much smaller, point-diffracted object, and almost certainly wouldn't be visible in the transmitted channel.</p>
<p>The obvious conclusion from this, is that the fluorescence signal is still within the vesicles and therefore is unlikely to have been released as a result of interaction with mRNA, drawing into question the conclusions of the paper. For more comments see the linked PubPeer thread.</p>
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<p>The movie has been processed in the following ways:</p>
<p>- A Gaussian bandpass filter (50px) in fourier space (transmitted channel) to correct uneven illumination.</p>
<p>- A median filter of 1px in the fluorescent channel to despeckle the image.</p>
<p>- The image was cropped to just a representative area and enlarged to 150% to aid visualisation.</p>
<p>This file is reproduced for non-commercial and educational use according to the PNAS copyright terms [https://web.archive.org/web/20151009081445/http://www.pnas.org/site/aboutpnas/rightperm.xhtml].</p
Supplemental Material, sj-docx-1-spp-10.1177_19485506211039388 - Mental Health Contributors Among Transgender People in a Non-WEIRD Society: Evidence From China
No full textSupplemental Material, sj-docx-1-spp-10.1177_19485506211039388 for Mental Health Contributors Among Transgender People in a Non-WEIRD Society: Evidence From China by Julia Spielmann, Siqi Feng, Daniel A. Briley and Chadly Stern in Social Psychological and Personality Science</p
Supplemental Material, sj-docx-2-spp-10.1177_19485506211039388 - Mental Health Contributors Among Transgender People in a Non-WEIRD Society: Evidence From China
No full textSupplemental Material, sj-docx-2-spp-10.1177_19485506211039388 for Mental Health Contributors Among Transgender People in a Non-WEIRD Society: Evidence From China by Julia Spielmann, Siqi Feng, Daniel A. Briley and Chadly Stern in Social Psychological and Personality Science</p
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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