Microbial applications for sustainable space exploration beyond low Earth orbit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the construction of the International Space Station, humans have been continuously living and working in space for 22 years. Microbial studies in space and other extreme environments on Earth have shown the ability for bacteria and fungi to adapt and change compared to "normal" conditions. Some of these changes, like biofilm formation, can impact astronaut health and spacecraft integrity in a negative way, while others, such as a propensity for plastic degradation, can promote self-sufficiency and sustainability in space. With the next era of space exploration upon us, which will see crewed missions to the Moon and Mars in the next 10 years, incorporating microbiology research into planning, decision-making, and mission design will be paramount to ensuring success of these long-duration missions. These can include astronaut microbiome studies to protect against infections, immune system dysfunction and bone deterioration, or biological in situ resource utilization (bISRU) studies that incorporate microbes to act as radiation shields, create electricity and establish robust plant habitats for fresh food and recycling of waste. In this review, information will be presented on the beneficial use of microbes in bioregenerative life support systems, their applicability to bISRU, and their capability to be genetically engineered for biotechnological space applications. In addition, we discuss the negative effect microbes and microbial communities may have on long-duration space travel and provide mitigation strategies to reduce their impact. Utilizing the benefits of microbes, while understanding their limitations, will help us explore deeper into space and develop sustainable human habitats on the Moon, Mars and beyond.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it