Science Goals and Mission Concept for a Landed Investigation of Mercury
Bibliographic record
Abstract
Abstract Mercury holds valuable clues to the distribution of elements at the birth of the solar system and how planets form and evolve in close proximity to their host stars. This Mercury Lander mission concept returns in situ measurements that address fundamental science questions raised by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission’s pioneering exploration of Mercury. Such measurements are needed to understand Mercury's unique mineralogy and geochemistry, characterize the proportionally massive core's structure, measure the planet's active and ancient magnetic fields at the surface, investigate the processes that alter the surface and produce the exosphere, and provide ground truth for remote data sets. The mission concept achieves one full Mercury year (∼88 Earth days) of surface operations with an 11-instrument, high-heritage payload delivered to a landing site within Mercury's widely distributed low-reflectance material, and it addresses science goals encompassing geochemistry, geophysics, the Mercury space environment, and geology. The spacecraft launches in 2035, and the four-stage flight system uses a solar electric propulsion cruise stage to reach Mercury in 2045. Landing is at dusk to meet thermal requirements, permitting ∼30 hr of sunlight for initial observations. The radioisotope-powered lander continues operations through the Mercury night. Direct-to-Earth communication is possible for the initial 3 weeks of landed operations, drops out for 6 weeks, and resumes for the final month. Thermal conditions exceed lander operating temperatures shortly after sunrise, ending operations. Approximately 11 GB of data are returned to Earth. The cost estimate demonstrates that a Mercury Lander mission is feasible and compelling as a New Frontiers–class mission.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".