1,720,987 research outputs found
What's the trouble with anthropic reasoning?
Selection effects in cosmology are often invoked to "explain" why some of the fundamental constant of Nature, and in particular the cosmological constant take on the value they do in our Universe. We briefly review this probabilistic "anthropic reasoning" and we argue that different (equally plausible) ways of assigning probabilities to candidate universes lead to totally different anthropic predictions, presenting an explicit example based on the total number of possible observations observers can carry out. We conclude that lacking a fundamental motivation for selecting one weighting scheme over another, anthropic reasoning cannot explain the value of A
Improved constraints on cosmological parameters from SNIa data
We present a new method based on a Bayesian hierarchical model to extract constraints on cosmological parameters from Type Ia supernova (SNIa) data obtained with the SALT-II light-curve fitter. We demonstrate with simulated data sets that our method delivers tighter statistical constraints on the cosmological parameters over 90 per cent of the time, that it reduces statistical bias typically by a factor of ∼2–3 and that it has better coverage properties than the usual χ2 approach. As a further benefit, a full posterior probability distribution for the dispersion of the intrinsic magnitude of SNe is obtained. We apply this method to recent SNIa data, and by combining them with cosmic microwave background and baryonic acoustic oscillations data, we obtain Ωm= 0.28 ± 0.02, ΩΛ= 0.73 ± 0.01 (assuming w=−1) and Ωm= 0.28 ± 0.01, w=−0.90 ± 0.05 (assuming flatness; statistical uncertainties only). We constrain the intrinsic dispersion of the B-band magnitude of the SNIa population, obtaining σintμ= 0.13 ± 0.01 mag. Applications to systematic uncertainties will be discussed in a forthcoming paper
The virtues of frugality - why cosmological observers should release their data slowly
Cosmologists will soon be in a unique position. Observational noise will gradually be replaced by cosmic variance as the dominant source of uncertainty in an increasing number of observations. We reflect on the ramifications for the discovery and verification of new models. If there are features in the full data set that call for a new model, there will be no subsequent observations to test that model's predictions. We give specific examples of the problem by discussing the pitfalls of model discovery by prior adjustment in the context of dark energy models and inflationary theories. We show how the gradual release of data can mitigate this difficulty, allowing anomalies to be identified and new models to be proposed and tested. We advocate that observers plan for the frugal release of data from future cosmic-variance-limited observations
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
Should we doubt the cosmological constant?
While Bayesian model selection is a useful tool to discriminate between competing cosmological models, it only gives a relative rather than an absolute measure of how good a model is. Bayesian doubt introduces an unknown benchmark model against which the known models are compared, thereby obtaining an absolute measure of model performance in a Bayesian framework. We apply this new methodology to the problem of the dark energy equation of state, comparing an absolute upper bound on the Bayesian evidence for a presently unknown dark energy model against a collection of known models including a flat Lambda cold dark matter (ΛCDM) scenario. We find a strong absolute upper bound to the Bayes factor B between the unknown model and ΛCDM, giving B≲ 5. The posterior probability for doubt is found to be less than 13 per cent (with a 1 per cent prior doubt) while the probability for ΛCDM rises from an initial 25 per cent to almost 70 per cent in light of the data. We conclude that ΛCDM remains a sufficient phenomenological description of currently available observations and that there is little statistical room for model improvement
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
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
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