1,720,988 research outputs found
A comparison of statistical methods for deriving occupancy estimates from machine learning outputs
The combination of autonomous recording units (ARUs) and machine learning enables scalable biodiversity monitoring. These data are often analysed using occupancy models, yet methods for integrating machine learning outputs with these models are rarely compared. Using the Yucatán black howler monkey as a case study, we evaluated four approaches for integrating ARU data and machine learning outputs into occupancy models: (i) standard occupancy models with verified data, and false-positive occupancy models using (ii) presence-absence data, (iii) counts of detections, and (iv) continuous classifier scores. We assessed estimator accuracy and the effects of decision threshold, temporal subsampling, and verification strategies. We found that classifier-guided listening with a standard occupancy model provided an accurate estimate with minimal verification effort. The false-positive models yielded similarly accurate estimates under specific conditions, but were sensitive to subjective choices including decision threshold. The inability to determine stable parameter choices a priori, coupled with the increased computational complexity of several models (i.e. the detection-count and continuous-score models), limits the practical application of false-positive models. In the case of a high-performance classifier and a readily detectable species, classifier-guided listening paired with a standard occupancy model provides a practical and efficient approach for accurately estimating occupancy
Going Beyond Counting First Authors in Author Co-citation Analysis
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
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We 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
Recommended from our members
Quantitative Ecology and the Conservation of Biodiversity: Species Richness, Abundance, and Extinction in Human-Altered Landscapes
The goal of conservation biology is to understand and prevent the loss of biological diversity. Modern conservation science relies heavily on four major quantitative methods: reserve site selection algorithms, species distribution models, population viability analyses, and species-area relationships. These methods, however, have several longstanding and unresolved shortcomings, including extensive data requirements, long computation times, and important simplifying assumptions, that limit their ability to inform conservation decisions in many real landscapes. This dissertation develops new approaches in quantitative ecology that address these shortcomings through the use of simulation modeling, probability theory, machine learning, modern statistics, and economic input-output analysis.Chapter 2 examines the optimal design of reserve networks for preventing extinction of terrestrial mammal species, demonstrating that the match between a species' body size and the spatial scale of a landscape can be used to determine which species will benefit from a clustered reserve network design. Chapter 3 derives two new macroecological metrics, similar to the species-area relationship, that provide probabilistic estimates of single-species extinction risks and community-wide extinction rates in landscapes undergoing habitat loss. Chapter 4 uses data from acoustic surveys to examine the road ecology of California bats, finding that total bat activity, and the activity of four common species, is decreased in the vicinity of large highways. Chapter 5 presents a "wildlife footprint" analysis that combines global bird and mammal range maps, data on the human appropriation of net primary productivity, and economic input-output tables to link specific human consumption activities to decreases in wild bird and mammal populations
Dispelling the Myths Behind First-author Citation Counts
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
- …
