The caveats section covers a lot of variations, between food samples and individual digestive tracts.
I've you've ever been diagnosed with anything that isn't mainstream, you're familiar with how much the medical community likes to stuff pegs of any shape into their favorite receptacles. A patient with ideopathic symptoms could be lying to you and sneaking food in the parking lot (I've known a couple of those), or they could be an anomaly. Singular or a few percent of the population. The world of genetics is vast and a handful of rare conditions can net you several examples within your Dunbar number.
We have a lot of people these days who don't seem to correspond directly to calories in/calories out. And unless they're absorbing energy from the universe, then something about our assumptions is broken.
At work I often find myself having to remind people that if your assumptions tell you that an event must be impossible, then it's not your eyes that are wrong but your assumptions. Half of debugging is being able to efficiently name your assumptions and sort them by probability x difficulty of verification.
If people aren't losing weight on diet soda, we need to be dismissing rules of thumb and directly testing patients instead of shrugging and saying, "exercise more, scrub." Which is a polite characterization of how medical people treat my obese friends.
I've you've ever been diagnosed with anything that isn't mainstream, you're familiar with how much the medical community likes to stuff pegs of any shape into their favorite receptacles. A patient with ideopathic symptoms could be lying to you and sneaking food in the parking lot (I've known a couple of those), or they could be an anomaly. Singular or a few percent of the population. The world of genetics is vast and a handful of rare conditions can net you several examples within your Dunbar number.
We have a lot of people these days who don't seem to correspond directly to calories in/calories out. And unless they're absorbing energy from the universe, then something about our assumptions is broken.
At work I often find myself having to remind people that if your assumptions tell you that an event must be impossible, then it's not your eyes that are wrong but your assumptions. Half of debugging is being able to efficiently name your assumptions and sort them by probability x difficulty of verification.
If people aren't losing weight on diet soda, we need to be dismissing rules of thumb and directly testing patients instead of shrugging and saying, "exercise more, scrub." Which is a polite characterization of how medical people treat my obese friends.