Similarities between Disaster Food and Space Food
Bibliographic record
Abstract
Disaster and space environments are similar in that they are closed environment, with limited lifelines. Here, we examined the similarity between disaster food and space food, to explore interactive problem-solving of food support for disaster and space environments. The Japan Disaster Food Certification Standards (Japan Disaster Food Society) and the Japanese Space Food Certification Standards (Japan Aerospace Exploration Agency) requirements and certified products, which were posted on the websites as of June 16, 2021, were compared. Certified products were classified into "staple foods," "main and/or side dishes," "milk and dairy products," "fruits," "confectionery and favorite beverages," "condiments," "dietary supplements," and "sets." Certification standards involved six items for Japan Disaster Food and eight items for Japanese Space Food. Most standards were similar. Concretely, both standards demanded room temperature storage, tough packaging and hygiene management in facilities. Both emphasized habitual food and easy eating. However, the best-by date was ≥6 mo for Japan Disaster Food, but ≥1.5 y for Japanese Space Food. In addition, Japanese Space Food required noted nutritious, food hygienic, eatable in space, cookable by specific equipment, endurable pressure by launch, and domestically produced food. There were 171 and 47 products of Japan Disaster Food and Japanese Space Food, respectively. Staple foods (pregelatinized rice, etc.) and main and/or side dishes were commonest among Japan Disaster Foods and Japanese Space Foods, respectively. It is possible to utilize of Space Food as Disaster Food, but there are some issues that must be cleared before "utilization of Disaster Food as Space Food."
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".