Radiometric Calibration Targets for the Mastcam-Z Camera on the Mars 2020 Rover Mission
Bibliographic record
Abstract
Abstract The Mastcam-Z Camera is a stereoscopic, multispectral camera with zoom capability on NASA’s Mars-2020 Perseverance rover. The Mastcam-Z relies on a set of two deck-mounted radiometric calibration targets to validate camera performance and to provide an instantaneous estimate of local irradiance and allow conversion of image data to units of reflectance (R∗ or I/F) on a tactical timescale. Here, we describe the heritage, design, and optical characterization of these targets and discuss their use during rover operations. The Mastcam-Z primary calibration target inherits features of camera calibration targets on the Mars Exploration Rovers, Phoenix and Mars Science Laboratory missions. This target will be regularly imaged during flight to accompany multispectral observations of the martian surface. The primary target consists of a gold-plated aluminum base, eight strong hollow-cylinder Sm2Co17 alloy permanent magnets mounted in the base, eight ceramic color and grayscale patches mounted over the magnets, four concentric, ceramic grayscale rings and a central aluminum shadow post (gnomon) painted with an IR-black paint. The magnets are expected to keep the central area of each patch relatively free of Martian aeolian dust. The Mastcam-Z secondary calibration target is a simple angled aluminum shelf carrying seven vertically mounted ceramic color and grayscale chips and seven identical, but horizontally mounted ceramic chips. The secondary target is intended to augment and validate the calibration-related information derived from the primary target. The Mastcam-Z radiometric calibration targets are critically important to achieving Mastcam-Z science objectives for spectroscopy and photometric properties.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".