Mars in the Visible to Near Infrared: Two Views of the Red Planet
Bibliographic record
Abstract
abstract: Remote sensing in visible to near-infrared wavelengths is an important tool for identifying and understanding compositional differences on planetary surfaces. Electronic transitions produce broad absorption bands that are often due to the presence of iron cations in crystalline mineral structures or amorphous phases. Mars’ iron-rich and variably oxidized surface provides an ideal environment for detecting spectral variations that can be related to differences in surface dust cover or the composition of the underlying bedrock. Several imaging cameras sent to Mars include the capability to selectively filter incoming light to discriminate between surface materials.\n\nAt the coarse spatial resolution provided by the wide-angle Mars Color Imager (MARCI) camera aboard the Mars Reconnaissance Orbiter (MRO), regional scale differences in reflectance at all wavelengths are dominated by the presence or absence of Fe3+-rich dust. The dust cover in many regions is highly variable, often with strong seasonal dependence although major storm events can redistribute dust in ways that significantly alter the albedo of large-scale regions outside of the normal annual cycle. Surface dust reservoirs represent an important part of the martian climate system and may play a critical role in the growth of regional dust storms to planet-wide scales. Detailed investigation of seasonal and secular changes permitted by repeated MARCI imaging coverage have allowed the surface dust coverage of the planet at large to be described and have revealed multiannual replenishing of regions historically associated with the growth of storms.\n\nFrom the ground, rover-based multispectral imaging acquired by the Mastcam cameras allows compositional discrimination between bedrock units and float material encountered along the Curiosity rover’s traverse across crater floor and lower Mt. Sharp units. Mastcam spectra indicate differences in primary mineralogy, the presence of iron-bearing alteration phases, and variations in iron oxidation state, which occur at specific locations along the rover’s traverse. These changes represent differences in the primary depositional environment and the action of later alteration by fluids circulating through fractures in the bedrock. Loose float rocks sample materials brought into the crater by fluvial or other processes. Mastcam observations provide important constraints on the geologic history of the Gale Crater site.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".