Two grant applications, a visual abstract and training the next generation of scientists: how a neuroscience lab works with EMET

"Overall, overwhelmingly positive. It's a very powerful tool… I am at least three to four times faster in terms of my overall academic work."

Dr. Gonzalo Quintana is a professor of psychology at the University of Chile in Santiago. He trained as a psychologist, took his PhD in neuroscience, and runs a group that works across both. Most of his output is literature review, manuscripts, grant applications, and the training of undergraduates and research assistants.

He did not arrive at EMET without a reference point. He had already worked with several other AI tools, free and paid, across multiple generations of them. Three things in EMET he had not seen in any of the others: the expert feature (saved, reusable instruction sets for queries), the dashboards (live, refreshable data visuals), and the prompt enhancer (enriched prompts from rough inputs).

Two grant applications, one of them well outside his expertise

Dr. Quintana has run two grants through EMET, both still under review. The first had been turned down twice already, so he gave it to EMET for a hard critique.

"It did provide things that I wasn't able to pick up in previous versions of my grant."

The second was a large equipment grant, on the order of 200,000 USD. Much of it had nothing to do with science: a procurement plan, transport, taxes, an implementation schedule, none of which he had written before.

"EMET allowed us not only to figure out how to write it, how to communicate it, and how to communicate it persuasively, but to put all of that into one very cohesive application."

Manuscripts, results and a visual abstract

On manuscripts he uses EMET across introduction, results, and discussion, handing it a figure, a table, or a spreadsheet of analysis and checking the interpretation against his own reading. Journals increasingly want visual abstracts, so he gave EMET a submitted study and asked for one.

"The visual abstract was just fantastic."

That is the pattern he keeps returning to. He asks for a task and gets back the thing standing next to it too.

"It always brings up something that is either between the lines, or it just takes it one step beyond."

Training the next set of scientists

The use case he was keenest to talk about was not his own work. It was his students.

"Writing and communicating effectively, and not just between scientists but also to the general public, those are skills that take years to develop."

He does not let EMET write for them. He sets the work, the student does it, and EMET gives structured feedback on what comes back: how sentences connect, whether a paragraph holds, where a construct discussed in the results was never set up in the introduction.

"It allows us to connect sentences to paragraph structure, to highlight what doesn't make sense or has not been incorporated in terms of the full manuscript."

Years of apprenticeship, compressed into a homework assignment.