Printed in U.S.A. Validation of a New Formula for Calculating the Energy Requirements
Bibliographic record
Abstract
ABSTRACT. In a previous study, we analyzed the roles of the estimated basal energy expenditure (EBEE) calculated by the Harris-Benedict equation, caloric intake (CI), total burn sur-face area (TBSA), body temperature (Temp) and number of post-burn days (PBD) in order to estimate the resting energy expenditure (EE) of burn patients. By multiple regression analysis we found that the measured EE (MEE) is best approx-imated by the following formula:-4343 + (10.5 x %TBSA) + (0.23 X CI) + (0.84 X EBEE) + (114 X Temp ("C))- (4.5 X PBD), r = 0.82, p < 0.001, (Toronto formula (TF)). To validate this, 10 patients with a mean TBSA of 49.1 k 5.5 % had their resting MEE done by indirect calorimetry when fed either by the TF or by 2 x EBEE. The caloric intake when on 2 x EBEE was 3260 k 45 kcal/day which significantly exceeded the MEE (2765 f 101 kcal/day, p < 0.001). The caloric intake when on
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.035 |
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".