MOSAIC: A Satellite Constellation to Enable Groundbreaking Mars Climate System Science and Prepare for Human Exploration
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
Abstract The Martian climate system has been revealed to rival the complexity of Earth’s. Over the last 20 yr, a fragmented and incomplete picture has emerged of its structure and variability; we remain largely ignorant of many of the physical processes driving matter and energy flow between and within Mars’ diverse climate domains. Mars Orbiters for Surface, Atmosphere, and Ionosphere Connections (MOSAIC) is a constellation of ten platforms focused on understanding these climate connections, with orbits and instruments tailored to observe the Martian climate system from three complementary perspectives. First, low-circular near-polar Sun-synchronous orbits (a large mothership and three smallsats spaced in local time) enable vertical profiling of wind, aerosols, water, and temperature, as well as mapping of surface and subsurface ice. Second, elliptical orbits sampling all of Mars’ plasma regions enable multipoint measurements necessary to understand mass/energy transport and ion-driven escape, also enabling, with the polar orbiters, dense radio occultation coverage. Last, longitudinally spaced areostationary orbits enable synoptic views of the lower atmosphere necessary to understand global and mesoscale dynamics, global views of the hydrogen and oxygen exospheres, and upstream measurements of space weather conditions. MOSAIC will characterize climate system variability diurnally and seasonally, on meso-, regional, and global scales, targeting the shallow subsurface all the way out to the solar wind, making many first-of-their-kind measurements. Importantly, these measurements will also prepare for human exploration and habitation of Mars by providing water resource prospecting, operational forecasting of dust and radiation hazards, and ionospheric communication/positioning disruptions.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| 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