Reflectance of Jezero Crater Floor: 1. Data Processing and Calibration of the Infrared Spectrometer (IRS) on SuperCam
Bibliographic record
Abstract
Abstract The Perseverance rover, Mars 2020 mission, landed on the surface of the Jezero crater, on 18 February 2021. This Martian crater is suspected to have hosted a paleolake as evidenced by the numerous detections of aqueously altered phases and thus is a promising candidate for the search for past Martian life. The SuperCam instrument, a collaboration by a consortium of American and European laboratories, plays a leading role in this investigation, thanks to its highly versatile payload providing rapid, synergistic, fine‐scale mineralogy, chemistry, and color imaging. After its landing, the first measurements of Martian targets with the infrared spectrometer of SuperCam (IRS) showed new instrumental behaviors that had to be characterized and calibrated to derive unbiased science data. The IRS radiometric response has thus been calibrated using periodic observations of the Aluwhite SuperCam Calibration Target (SCCT). Parasitic effects were understood and mitigated, and the instrumental dark and noise are characterized and modeled. The reflectance calibrated data products, provided periodically on the NASA Planetary Data System, are corrected for the main instrumental features. This radiometric calibration allowed us to study the 2.5 μm absorption band, which has been discovered in the Séítah unit and is associated with phyllosilicates‐carbonates mixtures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".