I gave up and went on tirzepatide, which mostly works. Down about 30 lbs. in two years and now on the highest dose. It does nothing for metabolism for me, actually clawing some back that I’d normally have in a falling phase. Discovering the antihistamines I take daily are correlated with 20 lbs. of gain in men was a big one, and I cut that dose back to 1⁄4. https://doi.org/10.1038/oby.2010.176
Created a Kalman model that filtered out day-to-day fluctuations to reconstitute true daily body composition, but tuning that model is a tradeoff. Adjusting to minimize Innovation consumes delicate theories. Lots of autocorrelations LLMs are eager to run with in an effort to truesight my monocausal fantasy.
Most candidate theories died. Gravitostat, wrong direction. Running beats walking by nothing at matched steps. Even walking was only a dozen calories an hour. Weight lifting multiple times a week barely added grams of muscle. Sleep duration, fiber, front-loading, none of it made a difference—something I’ve known intuitively for decades. Trying to reconcile my pre-tirz loss and regain and post-tirz loss with all the SURMOUNT trials’ loss and regain to find one model that explains all and quantifies how or what GLP-1s act on (suppressing a set point by x lbs. per mg that can only shift when weight is maintained for y time?).
Protein leverage disappearing on tirz is pretty interesting, but no simple control system yet. You’re welcome to burn any excess Fable tokens on the repo if you can get through its biosafety filters.
I gave up and went on tirzepatide, which mostly works. Down about 30 lbs. in two years and now on the highest dose. It does nothing for metabolism for me, actually clawing some back that I’d normally have in a falling phase. Discovering the antihistamines I take daily are correlated with 20 lbs. of gain in men was a big one, and I cut that dose back to 1⁄4. https://doi.org/10.1038/oby.2010.176
Created a Kalman model that filtered out day-to-day fluctuations to reconstitute true daily body composition, but tuning that model is a tradeoff. Adjusting to minimize Innovation consumes delicate theories. Lots of autocorrelations LLMs are eager to run with in an effort to truesight my monocausal fantasy.
Most candidate theories died. Gravitostat, wrong direction. Running beats walking by nothing at matched steps. Even walking was only a dozen calories an hour. Weight lifting multiple times a week barely added grams of muscle. Sleep duration, fiber, front-loading, none of it made a difference—something I’ve known intuitively for decades. Trying to reconcile my pre-tirz loss and regain and post-tirz loss with all the SURMOUNT trials’ loss and regain to find one model that explains all and quantifies how or what GLP-1s act on (suppressing a set point by x lbs. per mg that can only shift when weight is maintained for y time?).
Protein leverage disappearing on tirz is pretty interesting, but no simple control system yet. You’re welcome to burn any excess Fable tokens on the repo if you can get through its biosafety filters.
https://github.com/Lucent/health-data/blob/master/FINDINGS.md