Tech Lunar Toilet: A STEM Project with High School Students
Bibliographic record
Abstract
We performed an innovative STEM outreach project. High school students from the Colombian robotics’ designed a prototype of a Lunar Loo named Tech Lunar Toilet (TLT) that was part of the international HeroX-NASA Challenge. These experiences were possible thanks to a wonderful network of collaboration. As a result of this program, the students that participated were able to cultivate their curiosity, strengthen their scientific skills and increase their interest in pursuing careers in STEM fields. Simultaneously, they were able to contrast visual and instrumental data obtained from the robotics and new technologies that can be performed in the microgravity environments for future space explorations. The efficient TLT suction system will guarantee proper operation in both microgravity and lunar gravity. Most of the structure can be built in a 3D printer using PLA as a raw material. This polymer made from renewable resources with mechanical properties comparable to the petroleum-based ones will allow reducing the weight of the structure. We recognized that our project-based education is a powerful engine for development. We share our methodology for the construction of our TLT that can be used in microgravity. We also show the progression and impact of this innovative project of scientific dissemination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".