Do Patients Drink Enough Water? Actual Pure Water Intake Compared to the Theoretical Daily Rules of Drinking Eight 8-Ounce Glasses and Drinking Half Your Body Weight in Ounces
Bibliographic record
Abstract
Water is vital for virtually every bodily process, but many people don’t drink enough water. We assessed how much actual water, on average, was drank by 100 consecutive patients from a well-ness clinic. The average water intake was about five 8-ounce glasses of water a day. When compared to the “drink eight glasses of water a day” rule, our sample was 3 glasses short. When compared to the “drink half your body weight in ounces” rule, our sample was 6 glasses short. Chronic, unintentional dehydration is so common that it may be better to consider many “dehydration diseases” such as asthma and allergies as well as non-infectious conditions and chronic pains to be identified as “indicators of body thirst” and not the conditions that today are considered “diseases of unknown etiology”. Physiologically there are parameters of dehydration that can be measured prior to one feeling “thirsty”, and therefore, simply drinking “ad libitum” or by natural instinct may not be adequate. Patients need to be told to drink more water and to keep a mental daily tally to be sure to optimize their hydration status to better their health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".