Bibliographic record
Abstract
The Moon Village and similar concepts are strongly reliant on in situ resource utilisation (ISRU). There is great interest in harvesting solar power using locally leveraged in situ resources as an essential facet of in situ infrastructure. Traditionally, silicon-based photovoltaic cells have been assumed, preferably manufactured in situ using a 3D printing rover, but there are major difficulties with such scenarios. Solar cells require pre-processing of regolith and solar cell manufacture. We present an alternative lunar resource leveraged-solar power production system on the Moon which can yield high conversion efficiencies – solar Fresnel lens-thermionic conversion. The thermionic vacuum tube is constructed from lunar-derived materials and NiFe asteroidal ores on the Moon. Given that the majority of energy required for ISRU is thermal, thermionic conversion exploits this energy source directly. Silicates such as anorthite can be treated with acid to yield alumina and silicic acid in solution from which pure silica can be precipitated. Pure silica when heated to high temperature yields fused silica glass which is transparent – fused silica glass may be employed to manufacture Fresnel lenses and/or mirrors. Both silica and alumina may be input to the Metalysis Fray Farthing Chen Cambridge electrolytic process to yield near pure Si and near pure Al, respectively.
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.
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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".