Paper Review Records
All Paper Review Records
1 valid samples · Newest publication first
Review days = acceptance date − received date. PDF, DOI, and publisher-page sources are retained.
94
days
Electrophysiological features of acute inflammatory demyelinating polyneuropathy associated with SARS-CoV-2 infection
Authors
Antonino Uncini; Camillo Foresti; Barbara Frigeni; Benedetta Storti; Maria Cristina Servalli; Stefano Gazzina; Giuseppe Cosentino; Francesca Bianchi; Ubaldo Del Carro; Enrico Alfonsi; Stefano Cotti Piccinelli; Giovanni De Maria; Alessandro Padovani; Massimiliano Filosto; Luigi IppolitiShow moreShow less
Affiliations
1. Department of Neuroscience, Imaging and Clinical Sciences, University “G. d’Annunzio”, Chieti, Italy; 2. Neuropathophysiology, “Papa Giovanni XXIII” Hospital, Bergamo, Italy; 3. Neuropathophysiology, ASST Spedali Civili, Brescia, Italy; 4. Department of Brain and Behavioral Sciences, University of Pavia and IRCCS Mondino Foundation, Pavia, Italy; 5. Neurology and Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Vita Salute San Raffaele University, Milano, Italy; 6. IRCCS Mondino Foundation, Pavia, Italy; 7. Center for Neuromuscular Diseases, Unit of Neurology, ASST Spedali Civili and University of Brescia, Brescia, Italy; 8. Statistics Unit, Department of Economics, University “G. d’Annunzio”, Pescara, ItalyShow moreShow less
Expert Matching · Case Demo
Turn Your Submission Goalsinto a Verifiable Journal Plan
Share your field, deadline, and author profile. CrushSCI uses real review records to suggest a title direction, shortlist journals, and estimate timelines.
Client
I work in environmental engineering and need an SCI paper published within three months. I have no grant funding or prominent co-author. Which journals could I target?
CrushSCI
Yes. We will first screen for feasibility against the 90-day deadline, then identify comparable papers without grant support or prominent co-authors. The final shortlist will prioritize research quality and journal scope.
- Suggested title
- Machine Learning and Life-Cycle Assessment for Predicting and Optimizing Carbon Emissions in Urban Wastewater Treatment
- Database shortlist
- Environmental Technology & Innovation
SampleLatest 5 valid paper samples from 2026
Average review62 days
Median65 days