Mars and the ESA Science Programme - the case for Mars polar science
Bibliographic record
Abstract
Current plans within the European Space Agency (ESA) for the future investigation of Mars (after the ExoMars programme) are centred around participation in the Mars Sample Return (MSR) programme led by NASA. This programme is housed within the Human and Robotic Exploration (HRE) Directorate of ESA. This White Paper, in response to the Voyage 2050 call, focuses on the important scientific objectives for the investigation of Mars outside the present HRE planning. The achievement of these objectives by Science Directorate missions is entirely consistent with ESA's Science Programme. We illustrate this with a theme centred around the study of the Martian polar caps and the investigation of recent (Amazonian) climate change produced by known oscillations in Mars' orbital parameters. Deciphering the record of climate contained within the polar caps would allow us to learn about the climatic evolution of another planet over the past few to hundreds of millions of years, and also addresses the more general goal of investigating volatile-related dynamic processes in the Solar System.
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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".