132,538 research outputs found
Whale sex PAN-Logue : Whale sex
No full textRothenberg, D. Whale sex. PAN : philosophy activism nature. 2008; 5, 128-132
Sampling data accompanying "An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: Development and offline assessment for use in an aerosol-climate model"
No full text<p>Datasets recording sampling results, accompanying the manuscript <em>An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: Development and offline assessment for use in an aerosol-climate model, </em>Rothenberg, D. and Wang, C., submitted, GMD. Please see the included README for more details.</p>
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
parcel_model: Modernization and updates for Python 2/3 compatibility
No full text<p>This release denotes an overhaul of the model documentation and modernization of its codebase, instigated on the release of <a href="http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-15-0223.1">Rothenberg and Wang (2016)</a>. The scientific description of the model in that article is still accurate and is reflected in this release of the code, but the model has been processed to update documentation where out-of-date and to enable compatibility between Python 2 and Python 3.</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
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