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Record W4224436000 · doi:10.1016/j.aca.2022.339837

Homogeneity assessment of the SuperCam calibration targets onboard rover perseverance

2022· article· en· W4224436000 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytica Chimica Acta · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of Winnipeg
FundersMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaConsejería de Educación, Junta de Castilla y LeónUniversidad de ValladolidCentre National de la Recherche ScientifiqueEuskal Herriko UnibertsitateaUniversidad de MálagaEusko JaurlaritzaCarlsbergfondetCentre National d’Etudes SpatialesJunta de Castilla y LeónNational Aeronautics and Space Administration
KeywordsChemistryHomogeneity (statistics)AstrobiologyCalibrationRemote sensingAerospace engineeringGeologyStatistics

Abstract

fetched live from OpenAlex

The SuperCam instrument, onboard the Perseverance rover (Mars 2020 mission) is designed to perform remote analysis on the Martian surface employing several spectroscopic techniques such as Laser Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman (TRR), Time-Resolved Fluorescence (TRF) and Visible and Infrared (VISIR) reflectance. In addition, SuperCam also acquires high-resolution images using a color remote micro-imager (RMI) as well as sounds with its microphone. SuperCam has three main subsystems, the Mast Unit (MU) where the laser for chemical analysis and collection optics are housed, the Body Unit (BU) where the different spectrometers are located inside the rover, and the SuperCam Calibration Target (SCCT) located on the rover's deck to facilitate calibration tests at similar ambient conditions as the analyzed samples. To perform adequate calibrations on Mars, the 22 mineral samples included in the complex SCCT assembly must have a very homogeneous distribution of major and minor elements. The analysis and verification of such homogeneity for the 5-6 replicates of the samples included in the SCCT has been the aim of this work. To verify the physic-chemical homogeneity of the calibration targets, micro Energy Dispersive X-ray Fluorescence (EDXRF) imaging was first used on the whole surface of the targets, then the relative abundances of the detected elements were computed on 20 randomly distributed areas of 100 × 100 μm. For those targets showing a positive Raman response, micro-Raman spectroscopy imaging was performed on the whole surface of the targets at a resolution of 100 × 100 μm. The %RSD values (percent of relative standard deviation of mean values) for the major elements measured with EDXRF were compared with similar values obtained by two independent LIBS set-ups at spot sizes of 300 μm in diameter. The statistical analysis showed which elements were homogeneously distributed in the 22 mineral targets of the SCCT, providing their uncertainty values for further calibration. Moreover, nine of the 22 targets showed a good Raman response and their mineral distributions were also studied. Those targets can be also used for calibration purposes of the Raman part of SuperCam using the wavenumbers of their main Raman bands proposed in this work.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.248
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it