Spaceflight Exercise and Textile Laundering Machine for Improved Human Health
Bibliographic record
Abstract
The 52nd International Conference on Environmental Systems was held in Calgary, Canada, on 16 July 2023 through 20 July 2023.||Without a precedent to laundering clothes off-Earth, a preliminary solution space is required to develop a spaceflight laundry machine capable of operating in various gravity fields. With this paper's proposed solution space, human exercise to power a vibration agitation bladder, a closed-loop hydraulic system, and a wastewater sensor suite provide a desirable environment for quantifying waste-mass transfer away from textiles while reducing textile damage. Bond Graph Theory is used to evaluate how human power affects system and cleaning performance because it is amenable to the large variety of machine configurations humans can set and to the coupling expected within the different subsystems. Bond Graph simulation results reveal preliminary performance metrics, sensor types and placements, and the hardware significantly impacting the spaceflight exercise and textile laundering machine's performance. Last, this paper's methodology provides structure in maturing the machine's Spaceflight Technology Readiness Level beyond its current s
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".