Theories to test

• Derive a formula to smooth daily perturbations in weight from glycogen-water binding (water weight). A few days below RMR expell it and a few days above recapture it. Useful for more precise analysis of other points below.
• Make trendline fit for intake vs. weight that has slow-changing RMR variable to force a fit. Find what high/low RMR correlates with, like a macronutrient. Graph RMR over time.
• Make trendline fit for intake vs. weight but hold RMR constant and change the calories per gram of carbs, protein, fat (4, 4, 9) to force a fit (5, 3, 7?).
• Look for set point abruptly increasing or decreasing and examine the few days or weeks when it appeared to happen. Is it possible only multi-day binges can shift set-point up, like 3 days of 3000 calories? Do days of 3000 calories spread out cause no shift in set point?
• Possible that set point only moves up in the presence of protein to capture high-effort hunted meals? Studies showing 20% protein = 10% protein + 500 calories.
• Look for long runs (months) of stable weight (±3 lbs) and see if intake does not support no change, which would be evidence for a set point that can only drift under certain circumstances.
• Test gravitostat theory by computing foot-pounds exerted per day (current weight * steps) and seeing if that leads to less intake the following day.
• Use sleep/wake times to count hours of overlap with local sunrise/sunset and see if that corresponds to intake.
• Create a database of distinct foods eaten (there aren't many) and see if scaling their calories up or down produces a better fit, suggesting a misestimate of a frequent restaurant meal, or more interestingly, super fattening or near-zero calorie type foods like pistachios were predicted to be.
• Does eating over 1000 calories for breakfast and lunch combined predict a lower total for the day?
• There are runs of 6 months of keto, 1 month of low protein, 2 or 3 tries at potato only, weekend 60-hour fasts. Do these stand out in any way?
• Fiber consumed in breakfast+lunch inversely correlated with daily intake?
• What best predicts whether a day will become a binge (> 2800)? Sugar intake the previous day? Being below current set point?
• What conditions push the set point down? Are there magic months where I lose 3 lbs and don't regain it for a long time?

Very open to use of LLMs for the purpose of estimating other nutrient data. "The following food named x has nutrient profile y. Estimate ingredients and ratio of PUFA to MUFA." OpenAI API key available for these requests.