Nutrition as a military capability to deliver human advantage: more people, more ready, more of the time
Bibliographic record
Abstract
Soldiers must achieve high-level mission-preparedness to endure extended periods of physical and cognitive activity, with unpredictable recovery, in all environments. Nutrition provides the foundation for health and performance. Militaries have not maximised the strategic and financial value that considering nutrition as a military capability could deliver. A whole system approach to military nutrition, based on the prepare-perform-recover human capability cycle phases, is presented. Trainee nutrition requirements, through to very-high-readiness forces undertaking arduous roles at reach, must be specifically addressed. Promoting military performance diets in the prepare phase, through practitioner-supported nutrition education and food provision, will ensure mission readiness and mitigate ill health. Delivering nutrition in field settings in the perform phase-through smaller/lighter, nutritionally optimised rations and smart packaging technologies-will improve utility and minimise waste. Strategic dietary supplement use can provide a mission performance-enhancing adjunct to a food-first philosophy. Impact value chain analysis of military nutrition capability investments could support cost-benefit measurement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".