The Mars 2020 Perseverance Rover Mast Camera Zoom (Mastcam-Z) Multispectral, Stereoscopic Imaging Investigation
Bibliographic record
Abstract
Abstract Mastcam-Z is a multispectral, stereoscopic imaging investigation on the Mars 2020 mission’s Perseverance rover. Mastcam-Z consists of a pair of focusable, 4:1 zoomable cameras that provide broadband red/green/blue and narrowband 400-1000 nm color imaging with fields of view from 25.6° × 19.2° (26 mm focal length at 283 μrad/pixel) to 6.2° × 4.6° (110 mm focal length at 67.4 μrad/pixel). The cameras can resolve (≥ 5 pixels) ∼0.7 mm features at 2 m and ∼3.3 cm features at 100 m distance. Mastcam-Z shares significant heritage with the Mastcam instruments on the Mars Science Laboratory Curiosity rover. Each Mastcam-Z camera consists of zoom, focus, and filter wheel mechanisms and a 1648 × 1214 pixel charge-coupled device detector and electronics. The two Mastcam-Z cameras are mounted with a 24.4 cm stereo baseline and 2.3° total toe-in on a camera plate ∼2 m above the surface on the rover’s Remote Sensing Mast, which provides azimuth and elevation actuation. A separate digital electronics assembly inside the rover provides power, data processing and storage, and the interface to the rover computer. Primary and secondary Mastcam-Z calibration targets mounted on the rover top deck enable tactical reflectance calibration. Mastcam-Z multispectral, stereo, and panoramic images will be used to provide detailed morphology, topography, and geologic context along the rover’s traverse; constrain mineralogic, photometric, and physical properties of surface materials; monitor and characterize atmospheric and astronomical phenomena; and document the rover’s sample extraction and caching locations. Mastcam-Z images will also provide key engineering information to support sample selection and other rover driving and tool/instrument operations decisions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".