Newsroom

Today marks the public release of the LabMetrics beta. After analyzing over 500 labs in private testing, we are opening the database to help students quantify mentorship quality.

Key Features:

• M-Index V1: Our proprietary algorithm for weighting student co-authorships.
• Network Visualization: Interactive graphs powered by OpenAlex data.
• Privacy First: Anonymous reviews with no login required for reading.

This is an independent, open-source initiative.

To test the stability of M-index mentorship matrics across many labs, and examine if the proportion of labs analysed at a University affect mentorship matrics, we analysed ~100 labs at the ETH Zurich and University of Heidelberg. Remarkable stability was observed. Quantifiable results will follow.

Stay posted for further updates.

We have completed a massive indexing run covering major US and European universities. The database now includes co-authorship networks for PIs across Biology, Chemistry, and Computer Science departments.

Based on early feedback, we have adjusted the M-Index to weigh 'First Author' student papers 2x heavily compared to middle-author positions. This change better reflects the mentorship effort required to guide a student to a primary publication.