Context Camera Investigation on board the Mars Reconnaissance Orbiter
Bibliographic record
Abstract
The Context Camera (CTX) on the Mars Reconnaissance Orbiter (MRO) is a Facility Instrument (i.e., government‐furnished equipment operated by a science team not responsible for design and fabrication) designed, built, and operated by Malin Space Science Systems and the MRO Mars Color Imager team (MARCI). CTX will (1) provide context images for data acquired by other MRO instruments, (2) observe features of interest to NASA's Mars Exploration Program (e.g., candidate landing sites), and (3) conduct a scientific investigation, led by the MARCI team, of geologic, geomorphic, and meteorological processes on Mars. CTX consists of a digital electronics assembly; a 350 mm f/3.25 Schmidt‐type telescope of catadioptric optical design with a 5.7° field of view, providing a ∼30‐km‐wide swath from ∼290 km altitude; and a 5000‐element CCD with a band pass of 500–700 nm and 7 μ m pixels, giving ∼6 m/pixel spatial resolution from MRO's nearly circular, nearly polar mapping orbit. Raw data are transferred to the MRO spacecraft flight computer for processing (e.g., data compression) before transmission to Earth. The ground data system and operations are based on 9 years of Mars Global Surveyor Mars Orbiter Camera on‐orbit experience. CTX has been allocated 12% of the total MRO data return, or about ≥3 terabits for the nominal mission. This data volume would cover ∼9% of Mars at 6 m/pixel, but overlapping images (for stereo, mosaics, and observation of changes and meteorological events) will reduce this area. CTX acquired its first (instrument checkout) images of Mars on 24 March 2006.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".