ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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A phylodynamic workflow to rapidly gain insights into the dispersal history and dynamics of SARS-CoV-2 lineages
This article has 20 authors:Reviewed by ScreenIT
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Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks
This article has 6 authors:Reviewed by ScreenIT
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Characteristics of patients presenting, and not presenting, to the emergency department during the early days of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Impact of hospitalised patients with COVID-19 taking Renin-Angiotensin-Aldosterone System inhibitors: a systematic review and meta-analysis
This article has 3 authors:Reviewed by ScreenIT
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Significance of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio for predicting clinical outcomes in COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects
This article has 7 authors:Reviewed by ScreenIT
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Low PEEP Mechanical Ventilation and PaO2/FiO2 Ratio Evolution in COVID-19 Patients
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 detection in setting of viral swabs scarcity: Are MRSA swabs and viral swabs equivalent?
This article has 10 authors:Reviewed by ScreenIT
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Rapid Generation of Neutralizing Antibody Responses in COVID-19 Patients
This article has 38 authors:Reviewed by ScreenIT
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Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort
This article has 16 authors:Reviewed by ScreenIT