Assessment of Nutritional Intake During Space Flight and Space Flight Analogs
Bibliographic record
Abstract
Maintaining adequate nutrient intake during space flight is important not only to meet nutrient needs of astronauts but also to help counteract negative effects of space flight on the human body. Beyond these functions, food also provides psychosocial benefits throughout a mission. Dietary intake data from multiple space programs, including the Space Shuttle and the International Space Station, are discussed. These data arise from medical monitoring of dietary intake and crew health, as well as from research protocols designed to assess the role of diet in counteracting bone loss and other health concerns. Ground- based studies are conducted to better understand some of the negative issues related to space flight. Examples of ground-based studies are extended-duration bed rest studies, vitamin D supplementation studies in Antarctica during 6-month winterovers, and 10- to 14-day saturation diving missions on the floor of the ocean. The use of weighed food records, diet diaries, barcodes and food-frequency questionnaires to assess nutritional intake of space crewmembers is described. Provision of food and nutrients in space flight is important for many body systems including the cardiovascular, musculoskeletal, endocrine, and immune systems. Key areas of concern during long-duration space flight include loss of body mass, bone and muscle loss, radiation exposure and oxidative damage, nutrient intake during spacewalks (extravehicular activity), depletion of nutrient stores, and inadequate dietary intake. Initial experimental research studies using food and nutrition as a countermeasure to aid in mitigating these concerns are underway. Beyond their importance for the few individuals leaving the planet, these studies have significant implications for those remaining on Earth.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".