ChatGPT: five priorities for research

Health-care systems are rolling out artificial-intelligence tools for diagnosis and monitoring. But how reliable are the models?

NIH plans grant-review overhaul to reduce bias

An artificially intelligent first author presents many ethical questions—and could upend the publishing process.

Taking the pain out of data sharing

“Lab members are typically in charge of their own data and notes. But institutional memory is better served if the team works together...”

The fraught quest to account for sex in biology research

Implementation Updates for the New NIH Data Management and Sharing Policy

NIH Data Management and Sharing - Jan 2023: “although the policy might require researchers to spend extra time organizing their data, ... the potential long-term boost in public trust for science will justify the extra effort.”

Save the Date for the next PCRI Symposium! March 11, 2022 Event info and Registration —> #PCRISymposium

DataWorks! Data Management Plan Challenge —based on the 2023 NIH Data Management and Sharing Plan Requirements (NOT-OD-014).

“the larger spotlight on COVID-19 preprints has raised concerns the media and public could misconstrue the results of early studies as finalized science and use it to make personal health decisions”

The long-standing issue often occurs when the abbreviated form of a gene’s name is incorrectly recognized as a date and autocorrected as such by Excel or Google Sheets. e.g. SEPT4 (septin 4) and MARCH1 will be automatically changed to 4-Sep and 1-Mar.

New and Updated Resources Available to Help Design Rigorous Clinical Trials

Updated ARRIVE guidelines 2.0 for animal research. Endorsed by over 1000 journals

RT @HHS_ORI: Mentors, don’t forget that you are responsible for the #ResearchIntegrity of your team’s data! #MentoringMonth Find out more h…

Working on your next grant application? Check-out these tips for writing a winning grant application:

Don't forget to manage those citations! If you are using @LabArchives you can import citations directly from PubMed.

This looks like an interesting event on #SpreadingFacts. A livestream is available:

RT @StatModeling: In short, adding more animals to your experiment is fine. The problem is in using statistical significance to make decis…