Learn how WriteWise has already helped researchers write high-quality manuscripts.
From 1 to 5 papers in 1 year using WriteWise
PhD Student in Biotechnology Universidad Andrés Bello
“This tool solves practically all of the problems I had when writing scientific articles. WriteWise helps you to not only write a paper quicker, but also with higher quality."
Jorge is a highly productive PhD student; he is the coauthor of 11 papers.
During 2019, Jorge published five papers with the aid of the WriteWise prototype.
From 2015-2018, Jorge published an average of one paper per year.
Ready to submit her first review within 1 month
PhD Student in Environmental Sciences Universidad de Concepción
"WriteWise helps with key things like connectors, verb usage, what is in the content, what is the most important thing in your paper, the structure that you should follow to build a good paper, and that it is interesting and easy to read."
On track to graduate with her paper ready for submission
Maria eugenia romero
PhD Student in Agronomic Sciences Universidad de Concepción
"The first and most important difference between the WriteWise software and other tools that can be used to write scientific articles is that it is a very user-friendly software and allows you to save time. It helps you get through the tedious tasks of writing an article, which is the Achilles Heel of all doctorate students and post-graduates in general."
Focused on science because WriteWise helps him with papers
Research Assistant, Laboratory of Biotechnology Universidad Andrés Bello
"[WriteWise] primarily [helped] me...to write the first draft of my investigation so that it could then be published. This saved me time, in addition to having a better quality manuscript that I can present. So, this tool is going to help me more efficiently write in the future in the laboratory because I will not have to invest so much time and effort into writing a scientific article."
Her first review now ready to submit after using WriteWise
PhD Student in Cellular & Molecular Biology Universidad de Concepción
"Before, I did not know how to start. My ideas were scattered. WriteWise gave me insights on how to write a paper, helping me a lot with the structure."
First author for the first time with the support of WriteWise
PhD Student in Cellular & Molecular Biology Universidad de Concepción
"[WriteWise] is 100% recommended; it is easy to work with; it is very didactic, and, furthermore, you can move quickly in creating ideas and verb tenses. You can go back and self-correct with this program and advance very quickly. What’s more, if you have previously published without using this program, it can improve your writing, I believe, by 40 or 50%. So, I firmly recommend it."
Graduation within reach with a publication ready for submission
PhD Student in Biophysics & Computational Biology Universidad de Concepción
"In comparison to other software, this is trained with scientific papers. In other words, the parts about the context are exclusively for writing a scientific text or a research paper. Other options have tools to help you write grammatically correct, but not necessarily a scientific paper."
WriteWise is the result of two years of research and development!
How do we know that WriteWise works?
Because we have conducted quantitative, peer-reviewed studies of our own technology!
A novel machine learning model that guides graduate students to write more organized and structured texts
Javier Vera, Hector Allende-Cid, René Venegas, Sebastián Rodríguez, Wenceslao Palma, Sofía Zamora, Fernando Lillo, Humberto González, Ashley Van Cott, and Eduardo N. Fuentes. 2018. Molecular Biology of the Cell, 29:26.
Academic writing is one of the most valuable skills a scientist can develop. A primary challenge for graduate students is to coherently and concisely organize and present ideas within a manuscript. Writing a quality research manuscript requires transmitting the most relevant information through precise sentences that fulfill diverse communicational roles, ultimately resulting in a coherent, understandable text connected by cohesive mechanisms (e.g. lexical relationships between pairs of terms). Despite technological advances, the execution and teaching of the writing process have not similarly advanced. Therefore, a top priority for graduate programs is to implement new methodologies and technologies that aid students in communicating research advances. Through our investigation, we developed a novel, unsupervised machine-learning model applied to cell biology and biomedical texts that guides students in writing better organized and more structured texts.
Revealing the collaborative dynamics of a large-scale arXiv text collection by means of k-shell decomposition
Javier Vera, Wenceslao Palma, Hector Allende, Sebastian Rodriguez, Juan Pavez, and Eduardo Fuentes. 2019. NetSci-X: International Conference on Network Science.
In this work was shown how k − shell decomposition helps to understand the dynamics of the formation of the decentralized and collaborative language community defined by the electronic repository arXiv. Our results suggest that there are several global patterns that emerges from the microscopic activity of users sharing content. The growth of the collection of texts (and therefore of the associated networks) was (almost) completely governed by the outmost k −shells, which exponentially increased its size over time. Nevertheless, the size of the most dense set of nodes (Skmax ) tends to linearly increase its size. This points in the direction of the existence of an exponential accumulation of words that forces changes in the main discipline (computer science, in our case), represented by Skmax . These observations were confirmed by the behavior of the (normalized) critical index k∗ = arg maxk |Sk |, since it exponentially shifts to the outmost network layers. Further study should describe the relationship between the index k and the number of connected components of the k − shell Sk . Moreover, it is plausible to propose that the decentralized features of arXiv appear precisely at those external layers.
Sentence encoders as a method for helping users identify and improve semantic similarity in bio-medical text
Brayn Díaz, Juan Pavez, Sebastian Rodríguez, Wenceslao Palma, Hector Allende-Cid, Rene Venegas, and Eduardo N. Fuentes. 2019. 5th Workshop on Automatic Text and Corpus Processing.
We demonstrated the effectiveness of both the USE and BioSentVec as methods for helping users identify and improve semantic similarity between sentences in bio-medical texts. The shared tendencies between the models support sequential similarity as a metric to evaluate a text’s cohesion. With both methods outliers can be easily spotted, and then specific modifications in the sentences can be carried out depending on the type of outlier.
WriteWise: software that guides scientific writing
Eduardo N. Fuentes, Hector Allende-Cid, Sebastián Rodríguez, Rene Venegas, Juan Pavez, Wenceslao Palma, Ismael Figueroa, Sofia Zamora, Brayn Diaz, and Ashley VanCott. 2019. 5th Workshop on Automatic Text and Corpus Processing.
WriteWise represents the first commercially available advanced platform that provides user's help and feedback to improve scientific papers writing. This is thanks to the development of and advance textual data representation at different linguistic levels (e.g. words, sentences) through using cutting-edge machine-learning models and applied linguistics research.