Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)

Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be working with significant separation in time (particularly analysts, who may be working on data produced years earlier), and they typically communicate via published information (whether journal papers, technical notes, or websites). The complexity of the models, experiments, and methodologies, along with the diversity (and sometimes inexact nature) of information sources, can easily lead to misinterpretation of what was actually intended or done. In this paper we introduce a taxonomy of terms for more clearly defining numerical experiments, put it in the context of previous work on experimental ontologies, and describe how we have used it to document the experiments of the sixth phase for the Coupled Model Intercomparison Project (CMIP6). We describe how, through iteration with a range of CMIP6 stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions. We demonstrate how this process has added value to CMIP6 itself by (a) helping those devising experiments to be clear about their goals and their implementation, (b) making it easier for those executing experiments to know what is intended, (c) exposing interrelationships between experiments, and (d) making it clearer for third parties (data users) to understand the CMIP6 experiments. We conclude with some lessons learnt and how these may be applied to future CMIP phases as well as other modelling campaigns

Introduction, comparison, and validation of Meta-Essentials

We present a new tool for meta‐analysis, _Meta‐Essentials_, which is free of charge and easy to use. In this paper, we introduce the tool and compare its features to other tools for meta‐analysis.We also provide detailed information on the validation of the tool. Although free of charge and simple, _Meta‐Essentials_ automatically calculates effect sizes from a wide range of statistics and can be used for a wide range of meta‐analysis applications, including subgroup analysis, moderator analysis, and publication bias analyses. The confidence interval of the overall effect is automatically based on the Knapp‐Hartung adjustment of the DerSimonian‐Laird estimator. However, more advanced meta‐analysis methods such as meta‐analytical structural equation modelling and meta‐regression with multiple covariates are not available. In summary, _Meta‐Essentials_ may prove a valuable resource for meta‐analysts, including researchers, teachers, and students

Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study

Background: Systematic reviews and meta-analyses of binary outcomes are widespread in all areas of application. The odds ratio, in particular, is by far the most popular effect measure. However, the standard meta-analysis of odds ratios using a random-effects model has a number of potential problems. An attractive alternative approach for the meta-analysis of binary outcomes uses a class of generalized linear mixed models (GLMMs). GLMMs are believed to overcome the problems of the standard random-effects model because they use a correct binomial-normal likelihood. However, this belief is based on theoretical considerations, and no sufficient simulations have assessed the performance of GLMMs in meta-analysis. This gap may be due to the computational complexity of these models and the resulting considerable time requirements. Methods: The present study is the first to provide extensive simulations on the performance of four GLMM methods (models with fixed and random study effects and two conditional methods) for meta-analysis of odds ratios in comparison to the standard random effects model. Results: In our simulations, the hypergeometric-normal model provided less biased estimation of the heterogeneity variance than the standard random-effects meta-analysis using the restricted maximum likelihood (REML) estimation when the data were sparse, but the REML method performed similarly for the point estimation of the odds ratio, and better for the interval estimation. Conclusions: It is difficult to recommend the use of GLMMs in the practice of meta-analysis. The problem of finding uniformly good methods of the meta-analysis for binary outcomes is still open

Kajian Desain Fasad Baru Grand Royal Panghegar Bandung dalam Perspektif Arsitektur Posmodern

Each buildings has an identity that characterize and perspectives on the building. Identity is one of them formed from the development of architectural styles in the period specified. Arsitrektur postmodern is one of the architectural style that evolved in the 1970s and is a form of criticism of the modern architectural style. In the period of the year is considered a modern architectural style tends International and monotonous because applying the principles of functionalism. While the postmodern architecture appreciate the uniqueness of the locality of a place and accept the presence of ornaments and decorations. Grand Royal Panghegar Bandung is a building that respects the uniqueness of the locality, play around with the Art Deco ornaments matching combined with stylish modern architecture

Heterogeneity of Research Results: A New Perspective From Which to Assess and Promote Progress in Psychological Science

Heterogeneity emerges when multiple close or conceptual replications on the same subject produce results that vary more than expected from the sampling error. Here we argue that unexplained heterogeneity reflects a lack of coherence between the concepts applied and data observed and therefore a lack of understanding of the subject matter. Typical levels of heterogeneity thus offer a useful but neglected perspective on the levels of understanding achieved in psychological science. Focusing on continuous outcome variables, we surveyed heterogeneity in 150 meta-analyses from cognitive, organizational, and social psychology and 57 multiple close replications. Heterogeneity proved to be very high in meta-analyses, with powerful moderators being conspicuously absent. Population effects in the average meta-analysis vary from small to very large for reasons that are typically not understood. In contrast, heterogeneity was moderate in close replications. A newly identified relationship between heterogeneity and effect size allowed us to make predictions about expected heterogeneity levels. We discuss important implications for the formulation and evaluation of theories in psychology. On the basis of insights from the history and philosophy of science, we argue that the reduction of heterogeneity is important for progress in psychology and its practical applications, and we suggest changes to our collective research practice toward this end

Linking anthropogenic resources to wildlife-pathogen dynamics: a review and meta-analysis

Urbanisation and agriculture cause declines for many wildlife, but some species benefit from novelresources, especially food, provided in human-dominated habitats. Resulting shifts in wildlife ecol-ogy can alter infectious disease dynamics and create opportunities for cross-species transmission,yet predicting host–pathogen responses to resource provisioning is challenging. Factors enhancingtransmission, such as increased aggregation, could be offset by better host immunity due toimproved nutrition. Here, we conduct a review and meta-analysis to show that food provisioningresults in highly heterogeneous infection outcomes that depend on pathogen type and anthropo-genic food source. We also find empirical support for behavioural and immune mechanismsthrough which human-provided resources alter host exposure and tolerance to pathogens. Areview of recent theoretical models of resource provisioning and infection dynamics shows thatchanges in host contact rates and immunity produce strong non-linear responses in pathogen inva-sion and prevalence. By integrating results of our meta-analysis back into a theoretical frame-work, we find provisioning amplifies pathogen invasion under increased host aggregation andtolerance, but reduces transmission if provisioned food decreases dietary exposure to parasites.These results carry implications for wildlife disease management and highlight areas for futurework, such as how resource shifts might affect virulence evolution

New Perspectives on Nitrogen Fixation Measurements Using 15N2 Gas

Recently, the method widely used to determine 15N2 fixation rates in marine and freshwater environments was found to underestimate rates because the dissolution of the added 15N2 gas bubble in seawater takes longer than theoretically calculated. As a solution to the potential underestimate of rate measurements, the usage of the enriched water method was proposed to provide constant 15N2 enrichment. Still, the superiority of enriched water method over the previously used bubble injection remains inconclusive. To clarify this issue, we performed laboratory based experiments and implemented the results into an error analysis of 15N2 fixation rates. Moreover, we conducted a literature search on the comparison of the two methods to calculate a mean effect size using a meta-analysis approach. Our results indicate that the error potentially introduced by an equilibrium phase of the 15N2 gas is −72% at maximum for experiments with very short incubation times of 1 h. In contrast, the underestimation was negligible for incubations lasting 12–24 h (error is −0.2%). Our meta-analysis indicates that 84% of the measurements in the two groups will overlap and there is a 61% chance that a sample picked at random from the enriched water group will have a higher value than one picked at random from the bubble group. Overall, the underestimation of N2 fixation rates when using the bubble method relative to the enriched water method is highly dependent on incubation time and other experimental conditions and cannot be generalized