GREYBRAIN FIELDNOTES

Your many roles.
One method underneath.

One stream shows you something you can make this week. The other looks at what is being claimed, and what the evidence actually supports. Both end at a skill you can practise.

WHAT’S POSSIBLE · A useful workflowWHAT’S ADVANCING · Evidence in context

THE EDITORIAL LIBRARY · RECENT FIELDNOTES

What changed. What you can do about it.

Nothing matches these filters yet.

Choose another role or stream, or work through one of the standing exercises below.

THE EVERGREEN PRACTICE LIBRARY

Choose a role. Practise a skill.

Eight exercises that are always here, whichever hat you are wearing today.

EVERGREEN PRACTICE · THE SCIENTIST

A promising AI finding still needs a good study

The observation is yours. So is the original question. Explore how GenAI can help you shape the investigation around it.

The moment you recognise

An interesting observation. The beginnings of a research question.

Try it with this synthetic material

A fictional research team notices that students who voluntarily attend extra teaching sessions score higher on a later quiz. Attendance was not randomly assigned; prior attainment and motivation were not measured.

Make something useful

Separate observation from causal hypothesis. List confounders and compare two study designs that could test the question. Do not invent results.

Your check: Separate supplied facts from suggestions. Open the source, identify what is missing and record what you changed.

TWO MINUTES · NOTHING TO SIGN UP FOR

Your first win
starts here.

An AI draft can overclaim confidently, in fluent English, with no warning that it has done so. This is the check that keeps the doctor in the loop.

No sign-up. You keep the template.

THE JOURNAL CLUB LABGuided demo · fictional case

01Read the source
02Spot the leap
03Keep the method

First, what does the source actually say?

FICTIONAL STUDY BRIEF

48 residents attended a journal-club workshop. Their average appraisal quiz score rose from 6/10 before the workshop to 8/10 immediately afterwards.

No comparison group. No later follow-up. Patient outcomes were not measured.

Now imagine handing this to an AI and asking for a summary for tomorrow’s journal club. Your job is what comes next: checking what it hands back.

This example is prewritten. No live AI request or real study is involved.

Turn a useful habit
into something you can show.

Self-paced foundations. Private capstone work. An exam and assessed progression towards the IIHMR Bangalore certificate programme. Eligibility and programme terms apply.

Explore the learning and certificate pathway ↗