Evidence taught to a cohort.
Teaching multiplies whatever sourcing habits you model. Titrate keeps the literature behind a course organized, so what you teach carries its citations and next term starts from what you built.
Titrate is pre-launch. What is described here is what it is being built to do, with Jeff Casebolt, PhD.
The central question
Does power training (high-velocity/explosive-intent resistance training) reduce fall risk — measured either via functional-capacity/balance surrogate outcomes or via actual fall incidence — more effectively than traditional slow-velocity strength training or general exercise in older adults?
- Orr et al.2006n=112supports
- Sherrington et al.2019n=108 RCTssupports
- El Hadouchi et al.2022n=15 trialssupports
- Jiménez-Lupión et al.2023n=12 studiessupports
- Claudino et al.2021n=5 RCTscontradicts
- Sun et al.2021n=10 RCTsmixed
What this category has in common
Teaching is accountability at scale: every student inherits the sourcing standard you demonstrate. Course material and the literature behind it usually live in separate systems, and the link between them is the thing that decays first.
A workbench, not a chatbot.
Nothing here writes a confident paragraph for you to trust. There is no chat window. You keep the judgment; the tool keeps the trail back to the papers. It cannot hallucinate a citation because it does not generate citations at all — a claim points at a paper already sitting in your own library, or it points at nothing.
How Titrate works
Bring the papers, or start from the topic. Group them into the units you teach. Write positions with the citations attached. Build the course from those positions — a workspace holds eight surfaces, from the library to the module a student sees.
The whole mechanism, and what a workspace holdsTitrate is pre-launch.
Join the practitioner waitlistOne email when the first practitioner cohort opens. Nothing else.
