A hierarchical evaluation of space-based systems performance
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
Space-based systems (SBS) technology has been advancing rapidly in terms of capability, affordability, size, and reliability. As in the commercial sector, defence and military institutions are looking to improve their space capabilities by increasing the number of smaller, more affordable, and more capable satellites that are being put into service. The military is looking to extend these capabilities at the strategic level, the operational and tactical levels. Increasing the number of satellites inevitably increases the complexity of planning for and operating the resulting constellations. Therefore, the benefit of employing more satellites must be evaluated not only to justify the increase in complexity, but also to show the significant improvements that can be achieved. In this paper, we propose a method to evaluate the performance and role of different SBS within the context of intelligence, surveillance and reconnaissance (ISR). An example is also given to demonstrate how different numbers of SBS can improve baseline ISR capabilities.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it