1,720,962 research outputs found
Uncertainty of predictions in absorption spectroscopy: Modelling with quantile regression forest
No full textInternational audienceMachine learning modelling is becoming popular for estimating agricultural and environmental properties from their infrared spectra. Commonly in modelling with machine learning and in commercial software applications, however, uncertainty estimates of the prediction are seldom reported. Uncertainty quantification of variables predicted with infrared spectroscopy is yet highly relevant in a number of applications, such as in uncertainty propagation analyses studies or for drug exposure detection. In this paper, we report on the development and application of quantile regression forest to predict properties from infrared spectroscopic data along with a sample-specific estimate of the uncertainty. Quantile regression forest is a machine learning algorithm that builds on random forest and provides estimate of the mean but also of the full conditional distribution of the predicted variable. We illustrate the algorithm with two chemometric applications and evaluate the modelling approach for its ability for predict the variable of interest and quantify the uncertainty. Evaluation involved usual validation statistics but also the validation of the uncertainty with the prediction interval coverage probability calculated for various interval widths. We tested prediction and prediction uncertainty quantification of two soil properties (cation exchange capacity and total organic carbon) as well as the dry matter of mango. The results confirm the potential of quantile regression forests for prediction and uncertainty quantification of properties predicted from infrared spectroscopy data. In all cases, the predictions were accurate and sample-specific estimates of the uncertainty were obtained. Validation of the uncertainty showed that the interval width was too large, thus overestimating the uncertainty for most intervals. Nevertheless, we recommend its use for operational applications as well as in future software developments, in particular when the data inferred by the spectroscopic model are used in other applications
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
No full textWe 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
Modelling of soil multifunctionality across Europe
Full text linkSoils sustain a number of functions playing a key role in ecosystem functioning and providing a multitude of services to human society. While it is acknowledged that all soils are multifunctional, there is, to date, limited knowledge on how the supply of soil functions and their combination differ spatially with land use type, soil characteristics, climate and land use intensity at large geographical scales. We address this gap by quantifying five functions of major importance to European soils: (1) primary productivity, (2) water regulation, (3) climate regulation, (4) nutrient cycling and (5) provision of habitat for biodiversity. We built a multi-attribute semi-quantitative model with a hierarchical structure. The model is structured for the large-scale evaluation of soil functions and takes as input a set of indicators related to dynamic and stable soil properties, as well as climate, topography and management practices, and returns qualitative aggregated attributes representing the soil functions supply. Thresholds for the soil functions supply are obtained by statistical analysis coupled with expert knowledge and vary across European environmental zones. The model is tested utilizing a large pan-European dataset focused on cropland and grassland systems. Statistical distributions of soil functions supply are obtained alongside alpha- and beta-multifunctionality representing the diversity of soil functions represented at a sampling location and the unique contribution of the sampled site to the regional (i.e. NUTS3 level) soil functions supply, respectively. We found that the supply of soil functions varied greatly across landscapes in Europe and between environmental zones. Spatial patterns of the alpha- and beta-multifunctionality revealed hotspots of multifunctionality (alpha multifunctionality) but also sites providing a set of soil function delivery unique within the region (beta multifunctionality). Few sites are both unique and highly diverse. Our study set a baseline estimate of soil functions in Europe as a prerequisite to consider soil functions in environmental planning
Upscaling models for the large-scale assessment of soil functions
Full text linkThe characterization and assessment of soil functions is a prerequisite for agricultural and environmental policies aimed at soil health. However, there is a lack of satisfactory models for the assessment of soil functions supply to support national and intergovernmental initiatives. In this study we fill this gap by restructuring models developed to assess the multifunctionality of agricultural soils at the field scale. The multi-criteria decision models rely on soil properties, site characteristics and management information to assess the following five soil functions: (1) water regulation, (2) climate regulation, (3) nutrient cycling, (4) primary productivity and (5) provision of habitat for biodiversity. We develop models to assess soil functions supply at regional and national scales by adapting their structure to cope with the general lack of information on soil management at larger geographical scales. The restructured models are verified and a sensitivity analysis of the new model structure is performed. We further applied a comparison of the upscaled models with results from validated field-scale models using real data from 94 sites spanning across 13 European countries. We found that the upscaled models showed a similar sensitivity to the variability of the input data from the 94 sampling sites as the base models from which they were developed and that their overall supply is expected to be comparable. We describe the model structure of the upscaled models as well as their qualitative scales and integration rules. We propose the application of the models can serve for large-scale assessment of soil functions supply as part of soil health assessment for regional and national environmental and agricultural policies
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