Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why ...
Very Deep Convolutional Networks for Large-Scale Image Recognition
In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evalu...
The Measurement of Observer Agreement for Categorical Data
This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially invo...
Case Study Research: Design and Methods
"This new edition Case Study Research has been carefully revised, updated, and expanded while retaining virtually all of the features and coverage of the second edition. Robert ...
The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.
In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers awa...
Common method biases in behavioral research: A critical review of the literature and recommended remedies.
Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how t...
Electric Field Effect in Atomically Thin Carbon Films
We describe monocrystalline graphitic films, which are a few atoms thick but are nonetheless stable under ambient conditions, metallic, and of remarkably high quality. The films...
CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individu...
Scikit-learn: Machine Learning in Python
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focu...